Tue Nov 9 17:26:56 EST 2021 cd /home/basuia/Documents/mmvt_root/subjects/UC07 setenv SUBJECTS_DIR /home/basuia/Documents/mmvt_root/subjects /home/basuia/Documents/mmvt_root/freesurfer/bin/recon-all -i /home/basuia/Desktop/46462693/46462693_fMRI_20210623094933_2.nii -subjid UC07 -all -parallel subjid UC07 setenv SUBJECTS_DIR /home/basuia/Documents/mmvt_root/subjects FREESURFER_HOME /home/basuia/Documents/mmvt_root/freesurfer Actual FREESURFER_HOME /home/basuia/Documents/mmvt_root/freesurfer build-stamp.txt: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 Linux Ishita-Ubuntu 5.4.0-89-generic #100~18.04.1-Ubuntu SMP Wed Sep 29 10:59:42 UTC 2021 x86_64 x86_64 x86_64 GNU/Linux cputime unlimited filesize unlimited datasize unlimited stacksize 8192 kbytes coredumpsize 0 kbytes memoryuse unlimited vmemoryuse unlimited descriptors 1024 memorylocked 65536 kbytes maxproc 127257 maxlocks unlimited maxsignal 127257 maxmessage 819200 maxnice 0 maxrtprio 0 maxrttime unlimited total used free shared buff/cache available Mem: 31G 1.5G 28G 357M 1.3G 28G Swap: 29G 0B 29G ######################################## program versions used dev (freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185) dev ProgramName: lta_convert ProgramArguments: lta_convert -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_and ProgramArguments: mri_and -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_annotation2label ProgramArguments: mri_annotation2label -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_aparc2aseg ProgramArguments: mri_aparc2aseg -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_surf2volseg ProgramArguments: mri_surf2volseg -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_binarize ProgramArguments: mri_binarize -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_ca_label ProgramArguments: mri_ca_label -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_ca_normalize ProgramArguments: mri_ca_normalize -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_ca_register ProgramArguments: mri_ca_register -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_cc ProgramArguments: mri_cc -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_compute_overlap ProgramArguments: mri_compute_overlap -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_compute_seg_overlap ProgramArguments: mri_compute_seg_overlap -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_concat ProgramArguments: mri_concat -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_concatenate_lta ProgramArguments: mri_concatenate_lta -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 mri_convert -all-info ProgramName: mri_convert ProgramArguments: mri_convert -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_diff ProgramArguments: mri_diff -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_edit_wm_with_aseg ProgramArguments: mri_edit_wm_with_aseg -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_em_register ProgramArguments: mri_em_register -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_fill ProgramArguments: mri_fill -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_fuse_segmentations ProgramArguments: mri_fuse_segmentations -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_fwhm ProgramArguments: mri_fwhm -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_gcut ProgramArguments: mri_gcut -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_info ProgramArguments: mri_info -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_label2label ProgramArguments: mri_label2label -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:56-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_label2vol ProgramArguments: mri_label2vol -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_log_likelihood ProgramArguments: mri_log_likelihood -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_mask ProgramArguments: mri_mask -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_matrix_multiply ProgramArguments: mri_matrix_multiply -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_normalize ProgramArguments: mri_normalize -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_normalize_tp2 ProgramArguments: mri_normalize_tp2 -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_or ProgramArguments: mri_or -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_relabel_hypointensities ProgramArguments: mri_relabel_hypointensities -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_relabel_nonwm_hypos ProgramArguments: mri_relabel_nonwm_hypos -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_remove_neck ProgramArguments: mri_remove_neck -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 dev ProgramName: mri_robust_register ProgramArguments: mri_robust_register -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 dev ProgramName: mri_robust_template ProgramArguments: mri_robust_template -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_anatomical_stats ProgramArguments: mris_anatomical_stats -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_ca_label ProgramArguments: mris_ca_label -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_calc ProgramArguments: mris_calc -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_convert ProgramArguments: mris_convert -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_curvature ProgramArguments: mris_curvature -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_curvature_stats ProgramArguments: mris_curvature_stats -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_diff ProgramArguments: mris_diff -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_divide_parcellation ProgramArguments: mris_divide_parcellation -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_segment ProgramArguments: mri_segment -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_segstats ProgramArguments: mri_segstats -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_euler_number ProgramArguments: mris_euler_number -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_fix_topology ProgramArguments: mris_fix_topology -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_topo_fixer ProgramArguments: mris_topo_fixer -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_jacobian ProgramArguments: mris_jacobian -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_label2annot ProgramArguments: mris_label2annot -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_left_right_register ProgramArguments: mris_left_right_register -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_place_surface ProgramArguments: mris_place_surface -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mrisp_paint ProgramArguments: mrisp_paint -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_register ProgramArguments: mris_register -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_smooth ProgramArguments: mris_smooth -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_sphere ProgramArguments: mris_sphere -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_surface_stats ProgramArguments: mris_surface_stats -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_stats2seg ProgramArguments: mri_stats2seg -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_thickness ProgramArguments: mris_thickness -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_thickness_diff ProgramArguments: mris_thickness_diff -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_topo_fixer ProgramArguments: mris_topo_fixer -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_surf2surf ProgramArguments: mri_surf2surf -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_surf2vol ProgramArguments: mri_surf2vol -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_surfcluster ProgramArguments: mri_surfcluster -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_volmask ProgramArguments: mris_volmask -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_tessellate ProgramArguments: mri_tessellate -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_vol2surf ProgramArguments: mri_vol2surf -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_vol2vol ProgramArguments: mri_vol2vol -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_voldiff ProgramArguments: mri_voldiff -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_watershed ProgramArguments: mri_watershed -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: tkregister2 ProgramArguments: tkregister2_cmdl -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 mri_motion_correct.fsl dev mri_convert -all-info ProgramName: mri_convert ProgramArguments: mri_convert -all-info ProgramVersion: dev TimeStamp: 2021/11/09-22:26:57-GMT BuildTime: Aug 24 2021 08:56:39 BuildStamp: freesurfer-linux-ubuntu18_x86_64-dev-20210824-e101185 User: basuia Machine: Ishita-Ubuntu Platform: Linux PlatformVersion: 5.4.0-89-generic CompilerName: GCC CompilerVersion: 4.8.5 Program nu_correct, built from: Package MNI N3, version 1.12.0, compiled by nicks@terrier (x86_64-unknown-linux-gnu) on 2015-06-19 at 01:25:34 ####################################### GCADIR /home/basuia/Documents/mmvt_root/freesurfer/average GCA RB_all_2020-01-02.gca GCASkull RB_all_withskull_2020_01_02.gca AvgCurvTif folding.atlas.acfb40.noaparc.i12.2016-08-02.tif GCSDIR /home/basuia/Documents/mmvt_root/freesurfer/average GCS DKaparc.atlas.acfb40.noaparc.i12.2016-08-02.gcs ####################################### /home/basuia/Documents/mmvt_root/subjects/UC07 mri_convert /home/basuia/Desktop/46462693/46462693_fMRI_20210623094933_2.nii /home/basuia/Documents/mmvt_root/subjects/UC07/mri/orig/001.mgz mri_convert /home/basuia/Desktop/46462693/46462693_fMRI_20210623094933_2.nii /home/basuia/Documents/mmvt_root/subjects/UC07/mri/orig/001.mgz reading from /home/basuia/Desktop/46462693/46462693_fMRI_20210623094933_2.nii... TR=7.33, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (1, 0, 0) j_ras = (0, 1, 0) k_ras = (0, 0, 1) writing to /home/basuia/Documents/mmvt_root/subjects/UC07/mri/orig/001.mgz... @#@FSTIME 2021:11:09:17:26:57 mri_convert N 2 e 1.29 S 0.00 U 1.61 P 125% M 32612 F 3 R 6822 W 0 c 8 w 7 I 728 O 24112 L 0.13 0.22 0.25 @#@FSLOADPOST 2021:11:09:17:26:58 mri_convert N 2 0.13 0.22 0.25 #-------------------------------------------- #@# MotionCor Tue Nov 9 17:26:59 EST 2021 Found 1 runs /home/basuia/Documents/mmvt_root/subjects/UC07/mri/orig/001.mgz Checking for (invalid) multi-frame inputs... Only one run found so motion correction will not be performed. I'll copy the run to rawavg and continue. cp /home/basuia/Documents/mmvt_root/subjects/UC07/mri/orig/001.mgz /home/basuia/Documents/mmvt_root/subjects/UC07/mri/rawavg.mgz /home/basuia/Documents/mmvt_root/subjects/UC07 mri_convert /home/basuia/Documents/mmvt_root/subjects/UC07/mri/rawavg.mgz /home/basuia/Documents/mmvt_root/subjects/UC07/mri/orig.mgz --conform mri_convert /home/basuia/Documents/mmvt_root/subjects/UC07/mri/rawavg.mgz /home/basuia/Documents/mmvt_root/subjects/UC07/mri/orig.mgz --conform reading from /home/basuia/Documents/mmvt_root/subjects/UC07/mri/rawavg.mgz... TR=7.33, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (1, 0, 0) j_ras = (0, 1, 0) k_ras = (0, 0, 1) changing data type from short to uchar (noscale = 0)... MRIchangeType: Building histogram 0 26768 1000, flo=0, fhi=0.999, dest_type=0 Reslicing using trilinear interpolation writing to /home/basuia/Documents/mmvt_root/subjects/UC07/mri/orig.mgz... @#@FSTIME 2021:11:09:17:27:02 mri_convert N 3 e 3.97 S 0.04 U 4.25 P 108% M 45464 F 0 R 18280 W 0 c 13 w 4 I 0 O 10872 L 0.13 0.22 0.25 @#@FSLOADPOST 2021:11:09:17:27:06 mri_convert N 3 0.20 0.23 0.25 mri_add_xform_to_header -c /home/basuia/Documents/mmvt_root/subjects/UC07/mri/transforms/talairach.xfm /home/basuia/Documents/mmvt_root/subjects/UC07/mri/orig.mgz /home/basuia/Documents/mmvt_root/subjects/UC07/mri/orig.mgz INFO: extension is mgz @#@FSTIME 2021:11:09:17:27:06 mri_add_xform_to_header N 4 e 0.55 S 0.01 U 0.86 P 158% M 23316 F 14 R 4584 W 0 c 3 w 21 I 3112 O 10872 L 0.20 0.23 0.25 @#@FSLOADPOST 2021:11:09:17:27:06 mri_add_xform_to_header N 4 0.20 0.23 0.25 #-------------------------------------------- #@# Talairach Tue Nov 9 17:27:06 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/mri mri_nu_correct.mni --no-rescale --i orig.mgz --o orig_nu.mgz --ants-n4 --n 1 --proto-iters 1000 --distance 50 /usr/bin/bc /home/basuia/Documents/mmvt_root/subjects/UC07/mri /home/basuia/Documents/mmvt_root/freesurfer/bin/mri_nu_correct.mni --no-rescale --i orig.mgz --o orig_nu.mgz --ants-n4 --n 1 --proto-iters 1000 --distance 50 nIters 1 mri_nu_correct.mni dev Linux Ishita-Ubuntu 5.4.0-89-generic #100~18.04.1-Ubuntu SMP Wed Sep 29 10:59:42 UTC 2021 x86_64 x86_64 x86_64 GNU/Linux Tue Nov 9 17:27:06 EST 2021 tmpdir is ./tmp.mri_nu_correct.mni.4169 cd /home/basuia/Documents/mmvt_root/subjects/UC07/mri AntsN4BiasFieldCorrectionFs -i orig.mgz -o ./tmp.mri_nu_correct.mni.4169/nu0.mgz --dtype uchar AntsN4BiasFieldCorrectionFs done mri_convert ./tmp.mri_nu_correct.mni.4169/nu0.mgz orig_nu.mgz --like orig.mgz --conform mri_convert ./tmp.mri_nu_correct.mni.4169/nu0.mgz orig_nu.mgz --like orig.mgz --conform reading from ./tmp.mri_nu_correct.mni.4169/nu0.mgz... TR=7.33, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, 0, 0) j_ras = (0, 0, -1) k_ras = (0, 1, 0) INFO: transform src into the like-volume: orig.mgz writing to orig_nu.mgz... Tue Nov 9 17:30:08 EST 2021 mri_nu_correct.mni done @#@FSTIME 2021:11:09:17:27:06 mri_nu_correct.mni N 12 e 181.66 S 0.15 U 181.78 P 100% M 507296 F 19 R 149299 W 0 c 963 w 119 I 4352 O 20776 L 0.20 0.23 0.25 @#@FSLOADPOST 2021:11:09:17:30:08 mri_nu_correct.mni N 12 0.97 0.59 0.39 talairach_avi --i orig_nu.mgz --xfm transforms/talairach.auto.xfm talairach_avi log file is transforms/talairach_avi.log... mv -f /home/basuia/Documents/mmvt_root/subjects/UC07/mri/talsrcimg_to_711-2C_as_mni_average_305_t4_vox2vox.txt /home/basuia/Documents/mmvt_root/subjects/UC07/mri/transforms/talsrcimg_to_711-2C_as_mni_average_305_t4_vox2vox.txt Started at Tue Nov 9 17:30:08 EST 2021 Ended at Tue Nov 9 17:30:30 EST 2021 talairach_avi done @#@FSTIME 2021:11:09:17:30:08 talairach_avi N 4 e 22.42 S 0.76 U 15.92 P 74% M 255520 F 12 R 397299 W 0 c 94 w 378 I 271984 O 295272 L 0.97 0.59 0.39 @#@FSLOADPOST 2021:11:09:17:30:30 talairach_avi N 4 0.91 0.60 0.40 cp transforms/talairach.auto.xfm transforms/talairach.xfm lta_convert --src orig.mgz --trg /home/basuia/Documents/mmvt_root/freesurfer/average/mni305.cor.mgz --inxfm transforms/talairach.xfm --outlta transforms/talairach.xfm.lta --subject fsaverage --ltavox2vox dev --src: orig.mgz src image (geometry). --trg: /home/basuia/Documents/mmvt_root/freesurfer/average/mni305.cor.mgz trg image (geometry). --inmni: transforms/talairach.xfm input MNI/XFM transform. --outlta: transforms/talairach.xfm.lta output LTA. --s: fsaverage subject name --ltavox2vox: output LTA as VOX_TO_VOX transform. LTA read, type : 1 1.07298 0.00560 0.01733 -2.13547; -0.03695 0.98118 0.11303 -51.19102; -0.03346 -0.07825 1.03831 13.24757; 0.00000 0.00000 0.00000 1.00000; setting subject to fsaverage Writing LTA to file transforms/talairach.xfm.lta... lta_convert successful. #-------------------------------------------- #@# Talairach Failure Detection Tue Nov 9 17:30:33 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/mri talairach_afd -T 0.005 -xfm transforms/talairach.xfm talairach_afd: Talairach Transform: transforms/talairach.xfm OK (p=0.6995, pval=0.4932 >= threshold=0.0050) @#@FSTIME 2021:11:09:17:30:33 talairach_afd N 4 e 0.00 S 0.00 U 0.00 P 40% M 5608 F 10 R 199 W 0 c 0 w 17 I 2512 O 0 L 0.84 0.59 0.40 @#@FSLOADPOST 2021:11:09:17:30:33 talairach_afd N 4 0.84 0.59 0.40 awk -f /home/basuia/Documents/mmvt_root/freesurfer/bin/extract_talairach_avi_QA.awk /home/basuia/Documents/mmvt_root/subjects/UC07/mri/transforms/talairach_avi.log tal_QC_AZS /home/basuia/Documents/mmvt_root/subjects/UC07/mri/transforms/talairach_avi.log TalAviQA: 0.97606 z-score: 0 #-------------------------------------------- #@# Nu Intensity Correction Tue Nov 9 17:30:33 EST 2021 mri_nu_correct.mni --i orig.mgz --o nu.mgz --uchar transforms/talairach.xfm --n 2 --ants-n4 /usr/bin/bc /home/basuia/Documents/mmvt_root/subjects/UC07/mri /home/basuia/Documents/mmvt_root/freesurfer/bin/mri_nu_correct.mni --i orig.mgz --o nu.mgz --uchar transforms/talairach.xfm --n 2 --ants-n4 nIters 2 mri_nu_correct.mni dev Linux Ishita-Ubuntu 5.4.0-89-generic #100~18.04.1-Ubuntu SMP Wed Sep 29 10:59:42 UTC 2021 x86_64 x86_64 x86_64 GNU/Linux Tue Nov 9 17:30:33 EST 2021 tmpdir is ./tmp.mri_nu_correct.mni.5046 cd /home/basuia/Documents/mmvt_root/subjects/UC07/mri AntsN4BiasFieldCorrectionFs -i orig.mgz -o ./tmp.mri_nu_correct.mni.5046/nu0.mgz --dtype uchar AntsN4BiasFieldCorrectionFs done mri_binarize --i ./tmp.mri_nu_correct.mni.5046/nu0.mgz --min -1 --o ./tmp.mri_nu_correct.mni.5046/ones.mgz dev cwd /home/basuia/Documents/mmvt_root/subjects/UC07/mri cmdline mri_binarize --i ./tmp.mri_nu_correct.mni.5046/nu0.mgz --min -1 --o ./tmp.mri_nu_correct.mni.5046/ones.mgz sysname Linux hostname Ishita-Ubuntu machine x86_64 user basuia input ./tmp.mri_nu_correct.mni.5046/nu0.mgz frame 0 nErode3d 0 nErode2d 0 output ./tmp.mri_nu_correct.mni.5046/ones.mgz Binarizing based on threshold min -1 max +infinity binval 1 binvalnot 0 fstart = 0, fend = 0, nframes = 1 Starting parallel 1 Found 16777216 values in range Counting number of voxels in first frame Found 16777215 voxels in final mask Writing output to ./tmp.mri_nu_correct.mni.5046/ones.mgz Count: 16777215 16777215.000000 16777216 99.999994 mri_binarize done mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.5046/ones.mgz --i orig.mgz --sum ./tmp.mri_nu_correct.mni.5046/sum.junk --avgwf ./tmp.mri_nu_correct.mni.5046/input.mean.dat dev cwd cmdline mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.5046/ones.mgz --i orig.mgz --sum ./tmp.mri_nu_correct.mni.5046/sum.junk --avgwf ./tmp.mri_nu_correct.mni.5046/input.mean.dat sysname Linux hostname Ishita-Ubuntu machine x86_64 user basuia whitesurfname white UseRobust 0 Loading ./tmp.mri_nu_correct.mni.5046/ones.mgz Loading orig.mgz Voxel Volume is 1 mm^3 Generating list of segmentation ids Found 1 segmentations Computing statistics for each segmentation Reporting on 1 segmentations Using PrintSegStat Computing spatial average of each frame 0 Writing to ./tmp.mri_nu_correct.mni.5046/input.mean.dat mri_segstats done mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.5046/ones.mgz --i ./tmp.mri_nu_correct.mni.5046/nu0.mgz --sum ./tmp.mri_nu_correct.mni.5046/sum.junk --avgwf ./tmp.mri_nu_correct.mni.5046/output.mean.dat dev cwd cmdline mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.5046/ones.mgz --i ./tmp.mri_nu_correct.mni.5046/nu0.mgz --sum ./tmp.mri_nu_correct.mni.5046/sum.junk --avgwf ./tmp.mri_nu_correct.mni.5046/output.mean.dat sysname Linux hostname Ishita-Ubuntu machine x86_64 user basuia whitesurfname white UseRobust 0 Loading ./tmp.mri_nu_correct.mni.5046/ones.mgz Loading ./tmp.mri_nu_correct.mni.5046/nu0.mgz Voxel Volume is 1 mm^3 Generating list of segmentation ids Found 1 segmentations Computing statistics for each segmentation Reporting on 1 segmentations Using PrintSegStat Computing spatial average of each frame 0 Writing to ./tmp.mri_nu_correct.mni.5046/output.mean.dat mri_segstats done mris_calc -o ./tmp.mri_nu_correct.mni.5046/nu0.mgz ./tmp.mri_nu_correct.mni.5046/nu0.mgz mul 1.17497432619357002137 Saving result to './tmp.mri_nu_correct.mni.5046/nu0.mgz' (type = MGH ) [ ok ] mri_convert ./tmp.mri_nu_correct.mni.5046/nu0.mgz nu.mgz --like orig.mgz mri_convert ./tmp.mri_nu_correct.mni.5046/nu0.mgz nu.mgz --like orig.mgz reading from ./tmp.mri_nu_correct.mni.5046/nu0.mgz... TR=7.33, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, 0, 0) j_ras = (0, 0, -1) k_ras = (0, 1, 0) INFO: transform src into the like-volume: orig.mgz writing to nu.mgz... mri_make_uchar nu.mgz transforms/talairach.xfm nu.mgz type change took 0 minutes and 5 seconds. mapping ( 8, 98) to ( 3, 110) Tue Nov 9 17:33:53 EST 2021 mri_nu_correct.mni done @#@FSTIME 2021:11:09:17:30:33 mri_nu_correct.mni N 9 e 199.88 S 0.57 U 203.54 P 102% M 614296 F 27 R 560027 W 0 c 601 w 238 I 7304 O 51464 L 0.84 0.59 0.40 @#@FSLOADPOST 2021:11:09:17:33:53 mri_nu_correct.mni N 9 1.00 0.80 0.53 mri_add_xform_to_header -c /home/basuia/Documents/mmvt_root/subjects/UC07/mri/transforms/talairach.xfm nu.mgz nu.mgz INFO: extension is mgz @#@FSTIME 2021:11:09:17:33:53 mri_add_xform_to_header N 4 e 0.41 S 0.00 U 0.72 P 173% M 23480 F 1 R 4595 W 0 c 4 w 5 I 512 O 8304 L 1.00 0.80 0.53 @#@FSLOADPOST 2021:11:09:17:33:53 mri_add_xform_to_header N 4 1.00 0.80 0.53 #-------------------------------------------- #@# Intensity Normalization Tue Nov 9 17:33:53 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/mri mri_normalize -g 1 -seed 1234 -mprage nu.mgz T1.mgz using max gradient = 1.000 setting seed for random number genererator to 1234 assuming input volume is MGH (Van der Kouwe) MP-RAGE reading mri_src from nu.mgz... normalizing image... NOT doing gentle normalization with control points/label talairach transform 1.07298 0.00560 0.01733 -2.13547; -0.03695 0.98118 0.11303 -51.19102; -0.03346 -0.07825 1.03831 13.24757; 0.00000 0.00000 0.00000 1.00000; processing without aseg, no1d=0 MRInormInit(): INFO: Modifying talairach volume c_(r,a,s) based on average_305 MRInormalize(): MRIsplineNormalize(): npeaks = 16 Starting OpenSpline(): npoints = 16 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... Iterating 2 times --------------------------------- 3d normalization pass 1 of 2 white matter peak found at 110 white matter peak found at 101 gm peak at 76 (76), valley at 57 (57) csf peak at 38, setting threshold to 63 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... --------------------------------- 3d normalization pass 2 of 2 white matter peak found at 110 white matter peak found at 97 gm peak at 73 (73), valley at 53 (53) csf peak at 37, setting threshold to 61 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... Done iterating --------------------------------- writing output to T1.mgz 3D bias adjustment took 1 minutes and 13 seconds. @#@FSTIME 2021:11:09:17:33:53 mri_normalize N 7 e 73.89 S 0.23 U 84.09 P 114% M 568384 F 5 R 263609 W 0 c 237 w 18 I 1480 O 8592 L 1.00 0.80 0.53 @#@FSLOADPOST 2021:11:09:17:35:07 mri_normalize N 7 1.18 0.92 0.59 #-------------------------------------------- #@# Skull Stripping Tue Nov 9 17:35:07 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/mri mri_em_register -skull nu.mgz /home/basuia/Documents/mmvt_root/freesurfer/average/RB_all_withskull_2020_01_02.gca transforms/talairach_with_skull.lta aligning to atlas containing skull, setting unknown_nbr_spacing = 5 == Number of threads available to mri_em_register for OpenMP = 4 == reading 1 input volumes... logging results to talairach_with_skull.log reading '/home/basuia/Documents/mmvt_root/freesurfer/average/RB_all_withskull_2020_01_02.gca'... GCAread took 0 minutes and 1 seconds. average std = 23.0 using min determinant for regularization = 52.8 0 singular and 9205 ill-conditioned covariance matrices regularized reading 'nu.mgz'... freeing gibbs priors...done. accounting for voxel sizes in initial transform bounding unknown intensity as < 8.9 or > 556.0 total sample mean = 77.3 (1403 zeros) ************************************************ spacing=8, using 3292 sample points, tol=1.00e-05... ************************************************ register_mri: find_optimal_transform find_optimal_transform: nsamples 3292, passno 0, spacing 8 resetting wm mean[0]: 100 --> 108 resetting gm mean[0]: 61 --> 61 input volume #1 is the most T1-like using real data threshold=7.0 skull bounding box = (47, 47, 9) --> (216, 229, 226) finding center of left hemi white matter using (103, 108, 118) as brain centroid of Right_Cerebral_White_Matter... MRImask(): AllowDiffGeom = 1 mean wm in atlas = 108, using box (82,86,91) --> (123, 130,144) to find MRI wm before smoothing, mri peak at 101 robust fit to distribution - 103 +- 8.5 after smoothing, mri peak at 104, scaling input intensities by 1.038 scaling channel 0 by 1.03846 initial log_p = -4.645 ************************************************ First Search limited to translation only. ************************************************ max log p = -4.571695 @ (-10.526, -10.526, -10.526) max log p = -4.550993 @ (5.263, 5.263, 5.263) max log p = -4.540653 @ (2.632, -7.895, -2.632) max log p = -4.496879 @ (-1.316, 1.316, -1.316) max log p = -4.496065 @ (-1.974, -0.658, 0.658) max log p = -4.483046 @ (0.987, 0.329, 1.645) max log p = -4.483046 @ (0.000, 0.000, 0.000) max log p = -4.483046 @ (0.000, 0.000, 0.000) Found translation: (-4.9, -12.2, -6.9): log p = -4.483 **************************************** Nine parameter search. iteration 0 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-4.444, old_max_log_p =-4.483 (thresh=-4.5) 1.07500 0.00000 0.00000 -14.68697; 0.00000 1.06580 0.14032 -31.39108; 0.00000 -0.13053 0.99144 14.23999; 0.00000 0.00000 0.00000 1.00000; iteration took 0 minutes and 26 seconds. **************************************** Nine parameter search. iteration 1 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-4.414, old_max_log_p =-4.444 (thresh=-4.4) 1.07500 0.00000 0.00000 -14.68697; 0.00000 1.14574 0.15084 -44.40368; 0.00000 -0.13053 0.99144 14.23999; 0.00000 0.00000 0.00000 1.00000; iteration took 0 minutes and 26 seconds. **************************************** Nine parameter search. iteration 2 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-4.414, old_max_log_p =-4.414 (thresh=-4.4) 1.07500 0.00000 0.00000 -14.68697; 0.00000 1.14574 0.15084 -44.40368; 0.00000 -0.13053 0.99144 14.23999; 0.00000 0.00000 0.00000 1.00000; reducing scale to 0.2500 iteration took 0 minutes and 25 seconds. **************************************** Nine parameter search. iteration 3 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-4.388, old_max_log_p =-4.414 (thresh=-4.4) 1.05141 0.07615 -0.02017 -22.48556; -0.06543 1.09554 0.17794 -31.78747; 0.03445 -0.16459 0.96628 15.78659; 0.00000 0.00000 0.00000 1.00000; iteration took 0 minutes and 23 seconds. **************************************** Nine parameter search. iteration 4 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-4.379, old_max_log_p =-4.388 (thresh=-4.4) 1.07121 0.04369 -0.05800 -15.81273; -0.03394 1.12197 0.14828 -36.30516; 0.06785 -0.12709 0.98882 5.04714; 0.00000 0.00000 0.00000 1.00000; iteration took 0 minutes and 23 seconds. **************************************** Nine parameter search. iteration 5 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-4.375, old_max_log_p =-4.379 (thresh=-4.4) 1.05108 0.07476 -0.02036 -22.15591; -0.07032 1.14108 0.15183 -34.74282; 0.03215 -0.12604 0.97163 11.61683; 0.00000 0.00000 0.00000 1.00000; reducing scale to 0.0625 iteration took 0 minutes and 23 seconds. **************************************** Nine parameter search. iteration 6 nscales = 2 ... **************************************** Result so far: scale 0.062: max_log_p=-4.356, old_max_log_p =-4.375 (thresh=-4.4) 1.05288 0.07700 -0.03634 -19.91115; -0.07032 1.14108 0.15183 -34.74282; 0.04917 -0.12437 0.96775 9.57888; 0.00000 0.00000 0.00000 1.00000; iteration took 0 minutes and 21 seconds. **************************************** Nine parameter search. iteration 7 nscales = 2 ... **************************************** Result so far: scale 0.062: max_log_p=-4.353, old_max_log_p =-4.356 (thresh=-4.4) 1.05658 0.07727 -0.03647 -20.42136; -0.07032 1.14108 0.15183 -34.74282; 0.04905 -0.12407 0.96548 9.81698; 0.00000 0.00000 0.00000 1.00000; min search scale 0.025000 reached *********************************************** Computing MAP estimate using 3292 samples... *********************************************** dt = 5.00e-06, momentum=0.80, tol=1.00e-05 l_intensity = 1.0000 Aligning input volume to GCA... Transform matrix 1.05658 0.07727 -0.03647 -20.42136; -0.07032 1.14108 0.15183 -34.74282; 0.04905 -0.12407 0.96548 9.81698; 0.00000 0.00000 0.00000 1.00000; nsamples 3292 Quasinewton: input matrix 1.05658 0.07727 -0.03647 -20.42136; -0.07032 1.14108 0.15183 -34.74282; 0.04905 -0.12407 0.96548 9.81698; 0.00000 0.00000 0.00000 1.00000; IFLAG= -1 LINE SEARCH FAILED. SEE DOCUMENTATION OF ROUTINE MCSRCH ERROR RETURN OF LINE SEARCH: INFO= 4 POSSIBLE CAUSES: FUNCTION OR GRADIENT ARE INCORRECT OR INCORRECT TOLERANCESoutof QuasiNewtonEMA: 010: -log(p) = -0.0 tol 0.000010 Resulting transform: 1.05658 0.07727 -0.03647 -20.42136; -0.07032 1.14108 0.15183 -34.74282; 0.04905 -0.12407 0.96548 9.81698; 0.00000 0.00000 0.00000 1.00000; pass 1, spacing 8: log(p) = -4.353 (old=-4.645) transform before final EM align: 1.05658 0.07727 -0.03647 -20.42136; -0.07032 1.14108 0.15183 -34.74282; 0.04905 -0.12407 0.96548 9.81698; 0.00000 0.00000 0.00000 1.00000; ************************************************** EM alignment process ... Computing final MAP estimate using 364986 samples. ************************************************** dt = 5.00e-06, momentum=0.80, tol=1.00e-07 l_intensity = 1.0000 Aligning input volume to GCA... Transform matrix 1.05658 0.07727 -0.03647 -20.42136; -0.07032 1.14108 0.15183 -34.74282; 0.04905 -0.12407 0.96548 9.81698; 0.00000 0.00000 0.00000 1.00000; nsamples 364986 Quasinewton: input matrix 1.05658 0.07727 -0.03647 -20.42136; -0.07032 1.14108 0.15183 -34.74282; 0.04905 -0.12407 0.96548 9.81698; 0.00000 0.00000 0.00000 1.00000; IFLAG= -1 LINE SEARCH FAILED. SEE DOCUMENTATION OF ROUTINE MCSRCH ERROR RETURN OF LINE SEARCH: INFO= 6 POSSIBLE CAUSES: FUNCTION OR GRADIENT ARE INCORRECT OR INCORRECT TOLERANCESoutof QuasiNewtonEMA: 012: -log(p) = 4.7 tol 0.000000 final transform: 1.05658 0.07727 -0.03647 -20.42136; -0.07032 1.14108 0.15183 -34.74282; 0.04905 -0.12407 0.96548 9.81698; 0.00000 0.00000 0.00000 1.00000; writing output transformation to transforms/talairach_with_skull.lta... #VMPC# mri_em_register VmPeak 827740 FSRUNTIME@ mri_em_register 0.0648 hours 4 threads registration took 3 minutes and 53 seconds. @#@FSTIME 2021:11:09:17:35:07 mri_em_register N 4 e 233.44 S 0.47 U 815.40 P 349% M 629208 F 5 R 166680 W 0 c 1664 w 156 I 151112 O 32 L 1.18 0.92 0.59 @#@FSLOADPOST 2021:11:09:17:39:00 mri_em_register N 4 2.92 2.32 1.25 mri_watershed -T1 -brain_atlas /home/basuia/Documents/mmvt_root/freesurfer/average/RB_all_withskull_2020_01_02.gca transforms/talairach_with_skull.lta T1.mgz brainmask.auto.mgz Mode: T1 normalized volume Mode: Use the information of atlas (default parms, --help for details) ********************************************************* The input file is T1.mgz The output file is brainmask.auto.mgz Weighting the input with atlas information before watershed *************************WATERSHED************************** Sorting... first estimation of the COG coord: x=137 y=123 z=113 r=84 first estimation of the main basin volume: 2518477 voxels Looking for seedpoints 2 found in the cerebellum 18 found in the rest of the brain global maximum in x=160, y=117, z=78, Imax=255 CSF=20, WM_intensity=110, WM_VARIANCE=5 WM_MIN=110, WM_HALF_MIN=110, WM_HALF_MAX=110, WM_MAX=110 preflooding height equal to 10 percent done. Analyze... main basin size=9417337029 voxels, voxel volume =1.000 = 9417337029 mmm3 = 9417336.832 cm3 done. PostAnalyze...Basin Prior 167 basins merged thanks to atlas ***** 0 basin(s) merged in 1 iteration(s) ***** 0 voxel(s) added to the main basin done. Weighting the input with prior template ****************TEMPLATE DEFORMATION**************** second estimation of the COG coord: x=131,y=128, z=110, r=10166 iterations ^^^^^^^^ couldn't find WM with original limits - expanding ^^^^^^ GLOBAL CSF_MIN=1, CSF_intensity=2, CSF_MAX=17 , nb = 45612 RIGHT_CER CSF_MIN=1, CSF_intensity=2, CSF_MAX=5 , nb = 2934 LEFT_CER CSF_MIN=1, CSF_intensity=2, CSF_MAX=21 , nb = 2610 RIGHT_BRAIN CSF_MIN=1, CSF_intensity=2, CSF_MAX=16 , nb = 20052 LEFT_BRAIN CSF_MIN=1, CSF_intensity=2, CSF_MAX=15 , nb = 19260 OTHER CSF_MIN=0, CSF_intensity=13, CSF_MAX=63 , nb = 756 CSF_MAX TRANSITION GM_MIN GM GLOBAL before analyzing : 17, 32, 56, 80 after analyzing : 17, 48, 56, 56 RIGHT_CER before analyzing : 5, 11, 69, 95 after analyzing : 5, 49, 69, 60 LEFT_CER before analyzing : 21, 49, 68, 80 after analyzing : 21, 61, 68, 65 RIGHT_BRAIN before analyzing : 16, 29, 54, 80 after analyzing : 16, 45, 54, 53 LEFT_BRAIN before analyzing : 15, 28, 56, 84 after analyzing : 15, 46, 56, 55 OTHER before analyzing : 63, 58, 56, 80 after analyzing : 46, 58, 58, 63 mri_strip_skull: done peeling brain highly tesselated surface with 10242 vertices matching...61 iterations *********************VALIDATION********************* curvature mean = -0.013, std = 0.010 curvature mean = 73.035, std = 8.377 No Rigid alignment: -atlas Mode Off (basic atlas / no registration) before rotation: sse = 2.20, sigma = 3.33 after rotation: sse = 2.20, sigma = 3.33 Localization of inacurate regions: Erosion-Dilation steps the sse mean is 2.22, its var is 2.73 before Erosion-Dilatation 0.04% of inacurate vertices after Erosion-Dilatation 0.00% of inacurate vertices Validation of the shape of the surface done. Scaling of atlas fields onto current surface fields ********FINAL ITERATIVE TEMPLATE DEFORMATION******** Compute Local values csf/gray Fine Segmentation...41 iterations mri_strip_skull: done peeling brain Brain Size = 1865355 voxels, voxel volume = 1.000 mm3 = 1865355 mmm3 = 1865.355 cm3 ****************************** Saving brainmask.auto.mgz done mri_watershed utimesec 20.235185 mri_watershed stimesec 0.176481 mri_watershed ru_maxrss 814816 mri_watershed ru_ixrss 0 mri_watershed ru_idrss 0 mri_watershed ru_isrss 0 mri_watershed ru_minflt 206552 mri_watershed ru_majflt 7 mri_watershed ru_nswap 0 mri_watershed ru_inblock 9816 mri_watershed ru_oublock 3168 mri_watershed ru_msgsnd 0 mri_watershed ru_msgrcv 0 mri_watershed ru_nsignals 0 mri_watershed ru_nvcsw 389 mri_watershed ru_nivcsw 59 mri_watershed done @#@FSTIME 2021:11:09:17:39:00 mri_watershed N 6 e 13.22 S 0.19 U 20.23 P 154% M 814816 F 7 R 206554 W 0 c 59 w 390 I 9816 O 3168 L 2.92 2.32 1.25 @#@FSLOADPOST 2021:11:09:17:39:14 mri_watershed N 6 2.71 2.30 1.27 cp brainmask.auto.mgz brainmask.mgz #------------------------------------- #@# EM Registration Tue Nov 9 17:39:15 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/mri mri_em_register -uns 3 -mask brainmask.mgz nu.mgz /home/basuia/Documents/mmvt_root/freesurfer/average/RB_all_2020-01-02.gca transforms/talairach.lta setting unknown_nbr_spacing = 3 using MR volume brainmask.mgz to mask input volume... == Number of threads available to mri_em_register for OpenMP = 4 == reading 1 input volumes... logging results to talairach.log reading '/home/basuia/Documents/mmvt_root/freesurfer/average/RB_all_2020-01-02.gca'... GCAread took 0 minutes and 1 seconds. average std = 7.2 using min determinant for regularization = 5.2 0 singular and 884 ill-conditioned covariance matrices regularized reading 'nu.mgz'... MRImask(): AllowDiffGeom = 1 MRImask(): AllowDiffGeom = 1 MRImask(): AllowDiffGeom = 1 MRImask(): AllowDiffGeom = 1 MRImask(): AllowDiffGeom = 1 freeing gibbs priors...done. accounting for voxel sizes in initial transform bounding unknown intensity as < 5.9 or > 519.0 total sample mean = 79.1 (1017 zeros) ************************************************ spacing=8, using 2841 sample points, tol=1.00e-05... ************************************************ register_mri: find_optimal_transform find_optimal_transform: nsamples 2841, passno 0, spacing 8 resetting wm mean[0]: 98 --> 107 resetting gm mean[0]: 61 --> 61 input volume #1 is the most T1-like using real data threshold=19.0 skull bounding box = (64, 61, 25) --> (198, 192, 209) finding center of left hemi white matter using (109, 105, 117) as brain centroid of Right_Cerebral_White_Matter... MRImask(): AllowDiffGeom = 1 mean wm in atlas = 107, using box (93,89,94) --> (125, 121,139) to find MRI wm before smoothing, mri peak at 101 robust fit to distribution - 103 +- 7.4 after smoothing, mri peak at 104, scaling input intensities by 1.029 scaling channel 0 by 1.02885 initial log_p = -4.206 ************************************************ First Search limited to translation only. ************************************************ max log p = -4.051908 @ (-10.526, -10.526, -10.526) max log p = -3.945485 @ (5.263, 5.263, 5.263) max log p = -3.878443 @ (-2.632, -2.632, 2.632) max log p = -3.864562 @ (-1.316, -1.316, -1.316) max log p = -3.832788 @ (3.289, 0.658, -0.658) max log p = -3.832788 @ (0.000, 0.000, 0.000) max log p = -3.832788 @ (0.000, 0.000, 0.000) max log p = -3.832788 @ (0.000, 0.000, 0.000) Found translation: (-5.9, -8.6, -4.6): log p = -3.833 **************************************** Nine parameter search. iteration 0 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-3.808, old_max_log_p =-3.833 (thresh=-3.8) 1.00000 0.00000 0.00000 -5.92106; 0.00000 0.92500 0.00000 1.03558; 0.00000 0.00000 0.92500 3.64669; 0.00000 0.00000 0.00000 1.00000; iteration took 0 minutes and 19 seconds. **************************************** Nine parameter search. iteration 1 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-3.808, old_max_log_p =-3.808 (thresh=-3.8) 1.00000 0.00000 0.00000 -5.92106; 0.00000 0.92500 0.00000 1.03558; 0.00000 0.00000 0.92500 3.64669; 0.00000 0.00000 0.00000 1.00000; reducing scale to 0.2500 iteration took 0 minutes and 19 seconds. **************************************** Nine parameter search. iteration 2 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-3.697, old_max_log_p =-3.808 (thresh=-3.8) 1.03250 0.09395 0.00517 -22.69078; -0.10353 0.96836 0.09435 -4.96450; 0.00451 -0.09325 0.93775 15.56584; 0.00000 0.00000 0.00000 1.00000; iteration took 0 minutes and 19 seconds. **************************************** Nine parameter search. iteration 3 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-3.697, old_max_log_p =-3.697 (thresh=-3.7) 1.03250 0.09395 0.00517 -22.69078; -0.10353 0.96836 0.09435 -4.96450; 0.00451 -0.09325 0.93775 15.56584; 0.00000 0.00000 0.00000 1.00000; reducing scale to 0.0625 iteration took 0 minutes and 19 seconds. **************************************** Nine parameter search. iteration 4 nscales = 2 ... **************************************** Result so far: scale 0.062: max_log_p=-3.689, old_max_log_p =-3.697 (thresh=-3.7) 1.03371 0.09406 0.00517 -22.86556; -0.10365 0.96949 0.09446 -5.10977; 0.00450 -0.09303 0.93555 15.77644; 0.00000 0.00000 0.00000 1.00000; iteration took 0 minutes and 18 seconds. **************************************** Nine parameter search. iteration 5 nscales = 2 ... **************************************** Result so far: scale 0.062: max_log_p=-3.685, old_max_log_p =-3.689 (thresh=-3.7) 1.03341 0.08993 0.03566 -25.58376; -0.10320 0.96366 0.12473 -8.61546; -0.02584 -0.12726 0.92802 24.18416; 0.00000 0.00000 0.00000 1.00000; min search scale 0.025000 reached *********************************************** Computing MAP estimate using 2841 samples... *********************************************** dt = 5.00e-06, momentum=0.80, tol=1.00e-05 l_intensity = 1.0000 Aligning input volume to GCA... Transform matrix 1.03341 0.08993 0.03566 -25.58376; -0.10320 0.96366 0.12473 -8.61546; -0.02584 -0.12726 0.92802 24.18416; 0.00000 0.00000 0.00000 1.00000; nsamples 2841 Quasinewton: input matrix 1.03341 0.08993 0.03566 -25.58376; -0.10320 0.96366 0.12473 -8.61546; -0.02584 -0.12726 0.92802 24.18416; 0.00000 0.00000 0.00000 1.00000; IFLAG= -1 LINE SEARCH FAILED. SEE DOCUMENTATION OF ROUTINE MCSRCH ERROR RETURN OF LINE SEARCH: INFO= 3 POSSIBLE CAUSES: FUNCTION OR GRADIENT ARE INCORRECT OR INCORRECT TOLERANCESoutof QuasiNewtonEMA: 008: -log(p) = -0.0 tol 0.000010 Resulting transform: 1.03341 0.08993 0.03566 -25.58376; -0.10320 0.96366 0.12473 -8.61546; -0.02584 -0.12726 0.92802 24.18416; 0.00000 0.00000 0.00000 1.00000; pass 1, spacing 8: log(p) = -3.685 (old=-4.206) transform before final EM align: 1.03341 0.08993 0.03566 -25.58376; -0.10320 0.96366 0.12473 -8.61546; -0.02584 -0.12726 0.92802 24.18416; 0.00000 0.00000 0.00000 1.00000; ************************************************** EM alignment process ... Computing final MAP estimate using 315638 samples. ************************************************** dt = 5.00e-06, momentum=0.80, tol=1.00e-07 l_intensity = 1.0000 Aligning input volume to GCA... Transform matrix 1.03341 0.08993 0.03566 -25.58376; -0.10320 0.96366 0.12473 -8.61546; -0.02584 -0.12726 0.92802 24.18416; 0.00000 0.00000 0.00000 1.00000; nsamples 315638 Quasinewton: input matrix 1.03341 0.08993 0.03566 -25.58376; -0.10320 0.96366 0.12473 -8.61546; -0.02584 -0.12726 0.92802 24.18416; 0.00000 0.00000 0.00000 1.00000; IFLAG= -1 LINE SEARCH FAILED. SEE DOCUMENTATION OF ROUTINE MCSRCH ERROR RETURN OF LINE SEARCH: INFO= 6 POSSIBLE CAUSES: FUNCTION OR GRADIENT ARE INCORRECT OR INCORRECT TOLERANCESoutof QuasiNewtonEMA: 010: -log(p) = 4.1 tol 0.000000 final transform: 1.03341 0.08993 0.03566 -25.58376; -0.10320 0.96366 0.12473 -8.61546; -0.02584 -0.12726 0.92802 24.18416; 0.00000 0.00000 0.00000 1.00000; writing output transformation to transforms/talairach.lta... #VMPC# mri_em_register VmPeak 815192 FSRUNTIME@ mri_em_register 0.0397 hours 4 threads registration took 2 minutes and 23 seconds. @#@FSTIME 2021:11:09:17:39:15 mri_em_register N 7 e 143.07 S 0.41 U 495.80 P 346% M 616536 F 0 R 166677 W 0 c 692 w 123 I 139952 O 16 L 2.71 2.30 1.27 @#@FSLOADPOST 2021:11:09:17:41:38 mri_em_register N 7 3.35 2.76 1.59 #-------------------------------------- #@# CA Normalize Tue Nov 9 17:41:38 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/mri mri_ca_normalize -c ctrl_pts.mgz -mask brainmask.mgz nu.mgz /home/basuia/Documents/mmvt_root/freesurfer/average/RB_all_2020-01-02.gca transforms/talairach.lta norm.mgz writing control point volume to ctrl_pts.mgz using MR volume brainmask.mgz to mask input volume... reading 1 input volume reading atlas from '/home/basuia/Documents/mmvt_root/freesurfer/average/RB_all_2020-01-02.gca'... reading transform from 'transforms/talairach.lta'... reading input volume from nu.mgz... resetting wm mean[0]: 98 --> 107 resetting gm mean[0]: 61 --> 61 input volume #1 is the most T1-like using real data threshold=18.0 skull bounding box = (64, 61, 25) --> (198, 192, 209) finding center of left hemi white matter using (109, 105, 117) as brain centroid of Right_Cerebral_White_Matter... mean wm in atlas = 107, using box (93,89,94) --> (125, 121,139) to find MRI wm before smoothing, mri peak at 101 robust fit to distribution - 103 +- 7.4 after smoothing, mri peak at 104, scaling input intensities by 1.029 scaling channel 0 by 1.02885 using 246437 sample points... INFO: compute sample coordinates transform 1.03341 0.08993 0.03566 -25.58376; -0.10320 0.96366 0.12473 -8.61546; -0.02584 -0.12726 0.92802 24.18416; 0.00000 0.00000 0.00000 1.00000; INFO: transform used finding control points in Left_Cerebral_White_Matter.... found 40230 control points for structure... bounding box (130, 65, 27) --> (197, 185, 205) Left_Cerebral_White_Matter: limiting intensities to 107.0 --> 132.0 5 of 13 (38.5%) samples deleted finding control points in Right_Cerebral_White_Matter.... found 39478 control points for structure... bounding box (68, 65, 25) --> (135, 180, 204) Right_Cerebral_White_Matter: limiting intensities to 117.0 --> 132.0 8 of 9 (88.9%) samples deleted finding control points in Left_Cerebellum_White_Matter.... found 3105 control points for structure... bounding box (130, 152, 55) --> (176, 203, 113) finding control points in Right_Cerebellum_White_Matter.... found 2710 control points for structure... bounding box (85, 152, 51) --> (131, 196, 113) finding control points in Brain_Stem.... found 3475 control points for structure... bounding box (112, 143, 93) --> (147, 215, 125) Brain_Stem: limiting intensities to 96.0 --> 132.0 1 of 7 (14.3%) samples deleted using 29 total control points for intensity normalization... bias field = 0.811 +- 0.098 0 of 15 control points discarded finding control points in Left_Cerebral_White_Matter.... found 40230 control points for structure... bounding box (130, 65, 27) --> (197, 185, 205) Left_Cerebral_White_Matter: limiting intensities to 95.0 --> 132.0 68 of 168 (40.5%) samples deleted finding control points in Right_Cerebral_White_Matter.... found 39478 control points for structure... bounding box (68, 65, 25) --> (135, 180, 204) Right_Cerebral_White_Matter: limiting intensities to 101.0 --> 132.0 61 of 79 (77.2%) samples deleted finding control points in Left_Cerebellum_White_Matter.... found 3105 control points for structure... bounding box (130, 152, 55) --> (176, 203, 113) Left_Cerebellum_White_Matter: limiting intensities to 88.0 --> 132.0 21 of 32 (65.6%) samples deleted finding control points in Right_Cerebellum_White_Matter.... found 2710 control points for structure... bounding box (85, 152, 51) --> (131, 196, 113) Right_Cerebellum_White_Matter: limiting intensities to 88.0 --> 132.0 5 of 8 (62.5%) samples deleted finding control points in Brain_Stem.... found 3475 control points for structure... bounding box (112, 143, 93) --> (147, 215, 125) Brain_Stem: limiting intensities to 88.0 --> 132.0 41 of 63 (65.1%) samples deleted using 350 total control points for intensity normalization... bias field = 1.007 +- 0.076 0 of 151 control points discarded finding control points in Left_Cerebral_White_Matter.... found 40230 control points for structure... bounding box (130, 65, 27) --> (197, 185, 205) Left_Cerebral_White_Matter: limiting intensities to 88.0 --> 132.0 13 of 219 (5.9%) samples deleted finding control points in Right_Cerebral_White_Matter.... found 39478 control points for structure... bounding box (68, 65, 25) --> (135, 180, 204) Right_Cerebral_White_Matter: limiting intensities to 88.0 --> 132.0 55 of 242 (22.7%) samples deleted finding control points in Left_Cerebellum_White_Matter.... found 3105 control points for structure... bounding box (130, 152, 55) --> (176, 203, 113) Left_Cerebellum_White_Matter: limiting intensities to 88.0 --> 132.0 10 of 14 (71.4%) samples deleted finding control points in Right_Cerebellum_White_Matter.... found 2710 control points for structure... bounding box (85, 152, 51) --> (131, 196, 113) Right_Cerebellum_White_Matter: limiting intensities to 88.0 --> 132.0 10 of 15 (66.7%) samples deleted finding control points in Brain_Stem.... found 3475 control points for structure... bounding box (112, 143, 93) --> (147, 215, 125) Brain_Stem: limiting intensities to 88.0 --> 132.0 42 of 60 (70.0%) samples deleted using 550 total control points for intensity normalization... bias field = 1.051 +- 0.081 0 of 419 control points discarded writing normalized volume to norm.mgz... writing control points to ctrl_pts.mgz freeing GCA...done. normalization took 1 minutes and 7 seconds. @#@FSTIME 2021:11:09:17:41:38 mri_ca_normalize N 8 e 66.73 S 0.37 U 70.08 P 105% M 677660 F 5 R 408216 W 0 c 259 w 228 I 1352 O 3984 L 3.35 2.76 1.59 @#@FSLOADPOST 2021:11:09:17:42:44 mri_ca_normalize N 8 1.79 2.42 1.55 #-------------------------------------- #@# CA Reg Tue Nov 9 17:42:44 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/mri mri_ca_register -nobigventricles -T transforms/talairach.lta -align-after -mask brainmask.mgz norm.mgz /home/basuia/Documents/mmvt_root/freesurfer/average/RB_all_2020-01-02.gca transforms/talairach.m3z not handling expanded ventricles... using previously computed transform transforms/talairach.lta renormalizing sequences with structure alignment, equivalent to: -renormalize -regularize_mean 0.500 -regularize 0.500 using MR volume brainmask.mgz to mask input volume... == Number of threads available to mri_ca_register for OpenMP = 4 == reading 1 input volumes... logging results to talairach.log reading input volume 'norm.mgz'... reading GCA '/home/basuia/Documents/mmvt_root/freesurfer/average/RB_all_2020-01-02.gca'... label assignment complete, 0 changed (0.00%) freeing gibbs priors...done. average std[0] = 5.0 Starting GCAMregister() label assignment complete, 0 changed (0.00%) npasses = 1, nlevels = 6 #pass# 1 of 1 ************************ enabling zero nodes setting smoothness cost coefficient to 0.156 #GCAMreg# pass 0 level1 5 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.16 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=256, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.958015 #FOTS# QuadFit found better minimum quadopt=(dt=315.889,rms=0.85455) vs oldopt=(dt=369.92,rms=0.8582) #GCMRL# 0 dt 315.888634 rms 0.855 10.800% neg 0 invalid 762 tFOTS 6.4410 tGradient 2.6420 tsec 9.5590 #FOTS# QuadFit found better minimum quadopt=(dt=231.097,rms=0.829356) vs oldopt=(dt=92.48,rms=0.83863) #GCMRL# 1 dt 231.097276 rms 0.829 2.948% neg 0 invalid 762 tFOTS 6.4090 tGradient 2.8560 tsec 9.7500 #FOTS# QuadFit found better minimum quadopt=(dt=265.392,rms=0.81835) vs oldopt=(dt=369.92,rms=0.819723) #GCMRL# 2 dt 265.392491 rms 0.818 1.327% neg 0 invalid 762 tFOTS 6.5630 tGradient 2.9160 tsec 9.9760 #FOTS# QuadFit found better minimum quadopt=(dt=175.673,rms=0.811963) vs oldopt=(dt=92.48,rms=0.813757) #GCMRL# 3 dt 175.673469 rms 0.812 0.780% neg 0 invalid 762 tFOTS 6.4050 tGradient 2.8380 tsec 9.7230 #GCMRL# 4 dt 369.920000 rms 0.806 0.712% neg 0 invalid 762 tFOTS 6.1020 tGradient 2.6390 tsec 9.1950 #FOTS# QuadFit found better minimum quadopt=(dt=135.2,rms=0.803059) vs oldopt=(dt=92.48,rms=0.803607) #GCMRL# 5 dt 135.200000 rms 0.803 0.388% neg 0 invalid 762 tFOTS 6.8660 tGradient 2.7170 tsec 10.0000 #GCMRL# 6 dt 1479.680000 rms 0.795 0.952% neg 0 invalid 762 tFOTS 6.3550 tGradient 2.9030 tsec 9.7400 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.791196) vs oldopt=(dt=92.48,rms=0.791445) #GCMRL# 7 dt 129.472000 rms 0.791 0.530% neg 0 invalid 762 tFOTS 6.4910 tGradient 2.9000 tsec 9.8940 #FOTS# QuadFit found better minimum quadopt=(dt=295.936,rms=0.790487) vs oldopt=(dt=369.92,rms=0.790511) #GCMRL# 8 dt 295.936000 rms 0.790 0.000% neg 0 invalid 762 tFOTS 6.4760 tGradient 2.7820 tsec 9.7510 #GCMRL# 9 dt 295.936000 rms 0.790 0.065% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.1870 tsec 3.6750 #GCMRL# 10 dt 295.936000 rms 0.789 0.169% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7740 tsec 3.2750 #GCMRL# 11 dt 295.936000 rms 0.787 0.221% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.0420 tsec 3.5190 #GCMRL# 12 dt 295.936000 rms 0.784 0.307% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.1040 tsec 3.5920 #GCMRL# 13 dt 295.936000 rms 0.783 0.221% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8420 tsec 3.3280 #GCMRL# 14 dt 295.936000 rms 0.782 0.154% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6690 tsec 3.1640 #GCMRL# 15 dt 295.936000 rms 0.779 0.310% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.0480 tsec 3.5450 #GCMRL# 16 dt 295.936000 rms 0.778 0.185% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.0980 tsec 3.5890 #GCMRL# 17 dt 295.936000 rms 0.778 0.001% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7750 tsec 3.2760 #GCMRL# 18 dt 295.936000 rms 0.776 0.210% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.9580 tsec 3.4430 #GCMRL# 19 dt 295.936000 rms 0.774 0.229% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.9300 tsec 3.4120 #GCMRL# 20 dt 295.936000 rms 0.774 0.055% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.0880 tsec 3.5860 #GCMRL# 21 dt 295.936000 rms 0.773 0.083% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7530 tsec 3.2470 #GCMRL# 22 dt 295.936000 rms 0.772 0.198% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.9240 tsec 3.4270 #GCMRL# 23 dt 295.936000 rms 0.771 0.113% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.9470 tsec 3.3530 #GCMRL# 24 dt 295.936000 rms 0.771 0.017% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.9220 tsec 3.4220 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.770057) vs oldopt=(dt=92.48,rms=0.770171) #GCMRL# 25 dt 129.472000 rms 0.770 0.079% neg 0 invalid 762 tFOTS 6.5360 tGradient 3.0730 tsec 10.1070 #FOTS# QuadFit found better minimum quadopt=(dt=295.936,rms=0.769955) vs oldopt=(dt=369.92,rms=0.769967) #GCMRL# 26 dt 295.936000 rms 0.770 0.000% neg 0 invalid 762 tFOTS 6.8770 tGradient 2.6810 tsec 10.0610 #GCMRL# 27 dt 295.936000 rms 0.770 0.013% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.9730 tsec 3.4530 #GCAMreg# pass 0 level1 5 level2 1 tsec 172.817 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.16 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=256, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.770372 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.767232) vs oldopt=(dt=92.48,rms=0.767652) #GCMRL# 29 dt 129.472000 rms 0.767 0.408% neg 0 invalid 762 tFOTS 6.5260 tGradient 2.9440 tsec 9.9630 #FOTS# QuadFit found better minimum quadopt=(dt=295.936,rms=0.766438) vs oldopt=(dt=369.92,rms=0.766471) #GCMRL# 30 dt 295.936000 rms 0.766 0.000% neg 0 invalid 762 tFOTS 6.4750 tGradient 2.6200 tsec 9.5930 #GCMRL# 31 dt 295.936000 rms 0.766 0.080% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.9570 tsec 3.4480 #GCMRL# 32 dt 295.936000 rms 0.765 0.072% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8540 tsec 3.3170 #GCMRL# 33 dt 295.936000 rms 0.765 0.050% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8020 tsec 3.3060 #FOTS# QuadFit found better minimum quadopt=(dt=443.904,rms=0.76456) vs oldopt=(dt=369.92,rms=0.764569) setting smoothness cost coefficient to 0.615 #GCAMreg# pass 0 level1 4 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.62 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=64, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.785194 #FOTS# QuadFit found better minimum quadopt=(dt=36.288,rms=0.783092) vs oldopt=(dt=25.92,rms=0.783247) #GCMRL# 35 dt 36.288000 rms 0.783 0.268% neg 0 invalid 762 tFOTS 6.4370 tGradient 2.4100 tsec 9.3420 #FOTS# QuadFit found better minimum quadopt=(dt=36.288,rms=0.782119) vs oldopt=(dt=25.92,rms=0.782305) #GCMRL# 36 dt 36.288000 rms 0.782 0.000% neg 0 invalid 762 tFOTS 6.1140 tGradient 2.5220 tsec 9.1360 #GCMRL# 37 dt 36.288000 rms 0.781 0.129% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.4010 tsec 2.9020 #GCMRL# 38 dt 36.288000 rms 0.780 0.189% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.4910 tsec 2.9810 #GCMRL# 39 dt 36.288000 rms 0.778 0.173% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5980 tsec 3.0990 #GCMRL# 40 dt 36.288000 rms 0.776 0.247% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5120 tsec 2.9860 #GCMRL# 41 dt 36.288000 rms 0.774 0.312% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6110 tsec 3.1000 #GCMRL# 42 dt 36.288000 rms 0.771 0.353% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.4650 tsec 2.9480 #GCMRL# 43 dt 36.288000 rms 0.768 0.394% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7040 tsec 3.2080 #GCMRL# 44 dt 36.288000 rms 0.765 0.395% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5870 tsec 3.0920 #GCMRL# 45 dt 36.288000 rms 0.762 0.352% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6480 tsec 3.1490 #GCMRL# 46 dt 36.288000 rms 0.760 0.267% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.4650 tsec 2.9540 #GCMRL# 47 dt 36.288000 rms 0.759 0.177% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5590 tsec 3.0610 #GCMRL# 48 dt 36.288000 rms 0.758 0.137% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5540 tsec 3.0470 #GCMRL# 49 dt 36.288000 rms 0.757 0.133% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5340 tsec 3.0440 #GCMRL# 50 dt 36.288000 rms 0.756 0.105% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5130 tsec 3.0010 #GCMRL# 51 dt 36.288000 rms 0.756 0.050% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5160 tsec 3.0130 #FOTS# QuadFit found better minimum quadopt=(dt=9.072,rms=0.755822) vs oldopt=(dt=6.48,rms=0.755823) #GCMRL# 52 dt 9.072000 rms 0.756 0.000% neg 0 invalid 762 tFOTS 6.9880 tGradient 2.4030 tsec 9.8990 #GCMRL# 53 dt 9.072000 rms 0.756 0.001% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5090 tsec 3.0030 #GCAMreg# pass 0 level1 4 level2 1 tsec 83.347 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.62 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=64, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.756346 #FOTS# QuadFit found better minimum quadopt=(dt=36.288,rms=0.754937) vs oldopt=(dt=25.92,rms=0.755049) #GCMRL# 55 dt 36.288000 rms 0.755 0.186% neg 0 invalid 762 tFOTS 6.4860 tGradient 2.4600 tsec 9.4280 setting smoothness cost coefficient to 2.353 #GCAMreg# pass 0 level1 3 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=2.35 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=16, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.802986 #FOTS# QuadFit found better minimum quadopt=(dt=6.4,rms=0.799451) vs oldopt=(dt=8,rms=0.799675) #GCMRL# 57 dt 6.400000 rms 0.799 0.440% neg 0 invalid 762 tFOTS 6.1930 tGradient 2.7000 tsec 9.3760 #GCMRL# 58 dt 2.000000 rms 0.799 0.000% neg 0 invalid 762 tFOTS 6.1520 tGradient 2.3540 tsec 9.0180 #GCAMreg# pass 0 level1 3 level2 1 tsec 24.572 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=2.35 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=16, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.799778 #FOTS# QuadFit found better minimum quadopt=(dt=0.6,rms=0.79925) vs oldopt=(dt=0.5,rms=0.79925) #GCMRL# 60 dt 0.600000 rms 0.799 0.066% neg 0 invalid 762 tFOTS 6.1610 tGradient 2.2030 tsec 8.8420 #FOTS# QuadFit found better minimum quadopt=(dt=0.075,rms=0.799252) vs oldopt=(dt=0.125,rms=0.799252) setting smoothness cost coefficient to 8.000 #GCAMreg# pass 0 level1 2 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=8.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=4, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.891356 #FOTS# QuadFit found better minimum quadopt=(dt=2.9318,rms=0.866352) vs oldopt=(dt=2.88,rms=0.866358) #GCMRL# 62 dt 2.931803 rms 0.866 2.805% neg 0 invalid 762 tFOTS 6.2140 tGradient 2.2820 tsec 8.9920 #FOTS# QuadFit found better minimum quadopt=(dt=3.21287,rms=0.858502) vs oldopt=(dt=2.88,rms=0.858589) #GCMRL# 63 dt 3.212871 rms 0.859 0.906% neg 0 invalid 762 tFOTS 6.1610 tGradient 2.4330 tsec 9.0740 #FOTS# QuadFit found better minimum quadopt=(dt=2.23125,rms=0.85551) vs oldopt=(dt=2.88,rms=0.855769) #GCMRL# 64 dt 2.231250 rms 0.856 0.348% neg 0 invalid 762 tFOTS 6.2190 tGradient 2.3590 tsec 9.0250 #FOTS# QuadFit found better minimum quadopt=(dt=2.35088,rms=0.854372) vs oldopt=(dt=2.88,rms=0.854439) #GCMRL# 65 dt 2.350877 rms 0.854 0.000% neg 0 invalid 762 tFOTS 6.5030 tGradient 2.2300 tsec 9.2340 #GCMRL# 66 dt 2.350877 rms 0.854 0.095% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2280 tsec 2.7130 #GCAMreg# pass 0 level1 2 level2 1 tsec 45.218 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=8.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=4, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.854018 #GCMRL# 68 dt 0.000000 rms 0.854 0.055% neg 0 invalid 762 tFOTS 5.8160 tGradient 2.3520 tsec 8.6670 setting smoothness cost coefficient to 20.000 #GCAMreg# pass 0 level1 1 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=20.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=1, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.911198 #FOTS# QuadFit found better minimum quadopt=(dt=0.112,rms=0.910595) vs oldopt=(dt=0.08,rms=0.910609) #GCMRL# 70 dt 0.112000 rms 0.911 0.066% neg 0 invalid 762 tFOTS 6.1170 tGradient 2.1520 tsec 8.7620 #FOTS# QuadFit found better minimum quadopt=(dt=0.112,rms=0.910587) vs oldopt=(dt=0.08,rms=0.9106) #GCMRL# 71 dt 0.112000 rms 0.911 0.000% neg 0 invalid 762 tFOTS 6.1740 tGradient 2.0610 tsec 8.7280 #GCMRL# 72 dt 0.112000 rms 0.910 0.027% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.3380 tsec 2.8340 #GCMRL# 73 dt 0.112000 rms 0.910 0.023% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2840 tsec 2.7900 #GCMRL# 74 dt 0.112000 rms 0.910 0.042% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2650 tsec 2.7750 #GCMRL# 75 dt 0.112000 rms 0.909 0.060% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9840 tsec 2.4850 #GCMRL# 76 dt 0.112000 rms 0.908 0.116% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1900 tsec 2.6810 #GCMRL# 77 dt 0.112000 rms 0.907 0.152% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0940 tsec 2.5830 #GCMRL# 78 dt 0.112000 rms 0.905 0.152% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.4920 tsec 2.9890 #GCMRL# 79 dt 0.112000 rms 0.904 0.137% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0820 tsec 2.5860 #GCMRL# 80 dt 0.112000 rms 0.903 0.113% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.3720 tsec 2.8730 #GCMRL# 81 dt 0.112000 rms 0.902 0.092% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1950 tsec 2.7210 #GCMRL# 82 dt 1.280000 rms 0.901 0.179% neg 0 invalid 762 tFOTS 6.1860 tGradient 2.3890 tsec 9.0750 #GCMRL# 83 dt 0.320000 rms 0.900 0.000% neg 0 invalid 762 tFOTS 6.2860 tGradient 2.0550 tsec 8.8110 #GCMRL# 84 dt 0.320000 rms 0.899 0.112% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2620 tsec 2.7470 #GCMRL# 85 dt 0.320000 rms 0.898 0.053% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0660 tsec 2.5660 #GCAMreg# pass 0 level1 1 level2 1 tsec 74.044 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=20.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=1, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.898854 #FOTS# QuadFit found better minimum quadopt=(dt=0.096,rms=0.898349) vs oldopt=(dt=0.08,rms=0.89835) #GCMRL# 87 dt 0.096000 rms 0.898 0.056% neg 0 invalid 762 tFOTS 6.1480 tGradient 2.2770 tsec 8.9320 #FOTS# QuadFit found better minimum quadopt=(dt=0.112,rms=0.898331) vs oldopt=(dt=0.08,rms=0.898335) #GCMRL# 88 dt 0.112000 rms 0.898 0.000% neg 0 invalid 762 tFOTS 6.0940 tGradient 2.2640 tsec 8.8330 #GCMRL# 89 dt 0.112000 rms 0.898 0.005% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2420 tsec 2.7500 #GCMRL# 90 dt 0.112000 rms 0.898 0.004% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2720 tsec 2.7820 #GCMRL# 91 dt 0.112000 rms 0.898 0.007% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1150 tsec 2.5550 #GCMRL# 92 dt 0.112000 rms 0.898 0.011% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1450 tsec 2.6450 #GCMRL# 93 dt 0.112000 rms 0.898 0.011% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1520 tsec 2.6490 #GCMRL# 94 dt 0.112000 rms 0.898 0.016% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2320 tsec 2.6890 resetting metric properties... setting smoothness cost coefficient to 40.000 #GCAMreg# pass 0 level1 0 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=40.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=0, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.850844 #FOTS# QuadFit found better minimum quadopt=(dt=0.197523,rms=0.846387) vs oldopt=(dt=0.32,rms=0.847525) #GCMRL# 96 dt 0.197523 rms 0.846 0.524% neg 0 invalid 762 tFOTS 6.0950 tGradient 1.7320 tsec 8.3190 #GCMRL# 97 dt 0.020000 rms 0.846 0.000% neg 0 invalid 762 tFOTS 6.3120 tGradient 1.7300 tsec 8.5610 #GCAMreg# pass 0 level1 0 level2 1 tsec 22.36 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=40.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=0, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.84666 #GCMRL# 99 dt 0.020000 rms 0.846 0.070% neg 0 invalid 762 tFOTS 6.2180 tGradient 1.6360 tsec 8.3480 #GCMRL# 100 dt 0.050000 rms 0.846 0.000% neg 0 invalid 762 tFOTS 5.8300 tGradient 1.6810 tsec 8.0290 GCAMregister done in 9.72198 min Starting GCAmapRenormalizeWithAlignment() without scales renormalizing by structure alignment.... renormalizing input #0 gca peak = 0.10253 (16) mri peak = 0.10935 (39) Left_Lateral_Ventricle (4): linear fit = 1.88 x + 0.0 (1188 voxels, overlap=0.151) Left_Lateral_Ventricle (4): linear fit = 1.50 x + 0.0 (1188 voxels, peak = 30), gca=24.0 gca peak = 0.17690 (16) mri peak = 0.06221 (25) Right_Lateral_Ventricle (43): linear fit = 1.59 x + 0.0 (863 voxels, overlap=0.317) Right_Lateral_Ventricle (43): linear fit = 1.50 x + 0.0 (863 voxels, peak = 25), gca=24.0 gca peak = 0.28275 (96) mri peak = 0.04337 (94) Right_Pallidum (52): linear fit = 1.07 x + 0.0 (427 voxels, overlap=0.632) Right_Pallidum (52): linear fit = 1.07 x + 0.0 (427 voxels, peak = 102), gca=102.2 gca peak = 0.18948 (93) mri peak = 0.07663 (81) Left_Pallidum (13): linear fit = 0.86 x + 0.0 (281 voxels, overlap=0.161) Left_Pallidum (13): linear fit = 0.86 x + 0.0 (281 voxels, peak = 80), gca=79.5 gca peak = 0.20755 (55) mri peak = 0.08386 (69) Right_Hippocampus (53): linear fit = 1.20 x + 0.0 (398 voxels, overlap=0.140) Right_Hippocampus (53): linear fit = 1.20 x + 0.0 (398 voxels, peak = 66), gca=65.7 gca peak = 0.31831 (58) mri peak = 0.08748 (73) Left_Hippocampus (17): linear fit = 1.26 x + 0.0 (362 voxels, overlap=0.017) Left_Hippocampus (17): linear fit = 1.26 x + 0.0 (362 voxels, peak = 73), gca=73.4 gca peak = 0.11957 (102) mri peak = 0.05698 (101) Right_Cerebral_White_Matter (41): linear fit = 1.00 x + 0.0 (62113 voxels, overlap=0.979) Right_Cerebral_White_Matter (41): linear fit = 1.00 x + 0.0 (62113 voxels, peak = 103), gca=102.5 gca peak = 0.11429 (102) mri peak = 0.06389 (98) Left_Cerebral_White_Matter (2): linear fit = 1.00 x + 0.0 (63549 voxels, overlap=0.966) Left_Cerebral_White_Matter (2): linear fit = 1.00 x + 0.0 (63549 voxels, peak = 103), gca=102.5 gca peak = 0.14521 (59) mri peak = 0.04122 (83) Left_Cerebral_Cortex (3): linear fit = 1.48 x + 0.0 (19454 voxels, overlap=0.000) Left_Cerebral_Cortex (3): linear fit = 1.48 x + 0.0 (19454 voxels, peak = 87), gca=87.0 gca peak = 0.14336 (58) mri peak = 0.03766 (80) Right_Cerebral_Cortex (42): linear fit = 1.40 x + 0.0 (21319 voxels, overlap=0.000) Right_Cerebral_Cortex (42): linear fit = 1.40 x + 0.0 (21319 voxels, peak = 81), gca=81.5 gca peak = 0.13305 (70) mri peak = 0.08122 (85) Right_Caudate (50): linear fit = 1.30 x + 0.0 (627 voxels, overlap=0.024) Right_Caudate (50): linear fit = 1.30 x + 0.0 (627 voxels, peak = 91), gca=91.3 gca peak = 0.15761 (71) mri peak = 0.08289 (83) Left_Caudate (11): linear fit = 1.15 x + 0.0 (672 voxels, overlap=0.203) Left_Caudate (11): linear fit = 1.15 x + 0.0 (672 voxels, peak = 82), gca=82.0 gca peak = 0.13537 (57) mri peak = 0.04366 (78) Left_Cerebellum_Cortex (8): linear fit = 1.38 x + 0.0 (7322 voxels, overlap=0.001) Left_Cerebellum_Cortex (8): linear fit = 1.38 x + 0.0 (7322 voxels, peak = 79), gca=78.9 gca peak = 0.13487 (56) mri peak = 0.04535 (72) Right_Cerebellum_Cortex (47): linear fit = 1.27 x + 0.0 (9724 voxels, overlap=0.003) Right_Cerebellum_Cortex (47): linear fit = 1.27 x + 0.0 (9724 voxels, peak = 71), gca=71.4 gca peak = 0.19040 (84) mri peak = 0.03561 (69) Left_Cerebellum_White_Matter (7): linear fit = 0.90 x + 0.0 (4114 voxels, overlap=0.378) Left_Cerebellum_White_Matter (7): linear fit = 0.90 x + 0.0 (4114 voxels, peak = 76), gca=76.0 gca peak = 0.18871 (83) mri peak = 0.04945 (67) Right_Cerebellum_White_Matter (46): linear fit = 0.86 x + 0.0 (4533 voxels, overlap=0.762) Right_Cerebellum_White_Matter (46): linear fit = 0.86 x + 0.0 (4533 voxels, peak = 71), gca=71.0 gca peak = 0.24248 (57) mri peak = 0.07345 (77) Left_Amygdala (18): linear fit = 1.33 x + 0.0 (195 voxels, overlap=0.069) Left_Amygdala (18): linear fit = 1.33 x + 0.0 (195 voxels, peak = 76), gca=75.5 gca peak = 0.35833 (56) mri peak = 0.08812 (65) Right_Amygdala (54): linear fit = 1.13 x + 0.0 (380 voxels, overlap=0.316) Right_Amygdala (54): linear fit = 1.13 x + 0.0 (380 voxels, peak = 64), gca=63.6 gca peak = 0.12897 (85) mri peak = 0.05684 (95) Left_Thalamus (10): linear fit = 1.12 x + 0.0 (3028 voxels, overlap=0.592) Left_Thalamus (10): linear fit = 1.12 x + 0.0 (3028 voxels, peak = 96), gca=95.6 gca peak = 0.13127 (83) mri peak = 0.06001 (88) Right_Thalamus (49): linear fit = 1.08 x + 0.0 (2710 voxels, overlap=0.860) Right_Thalamus (49): linear fit = 1.08 x + 0.0 (2710 voxels, peak = 89), gca=89.2 gca peak = 0.12974 (78) mri peak = 0.07125 (92) Left_Putamen (12): linear fit = 1.15 x + 0.0 (1205 voxels, overlap=0.122) Left_Putamen (12): linear fit = 1.15 x + 0.0 (1205 voxels, peak = 90), gca=90.1 gca peak = 0.17796 (79) mri peak = 0.06345 (89) Right_Putamen (51): linear fit = 1.10 x + 0.0 (1446 voxels, overlap=0.701) Right_Putamen (51): linear fit = 1.10 x + 0.0 (1446 voxels, peak = 87), gca=86.5 gca peak = 0.10999 (80) mri peak = 0.07933 (80) Brain_Stem (16): linear fit = 1.10 x + 0.0 (4726 voxels, overlap=0.416) Brain_Stem (16): linear fit = 1.10 x + 0.0 (4726 voxels, peak = 88), gca=87.6 gca peak = 0.13215 (88) mri peak = 0.08086 (95) Right_VentralDC (60): linear fit = 1.09 x + 0.0 (563 voxels, overlap=0.324) Right_VentralDC (60): linear fit = 1.09 x + 0.0 (563 voxels, peak = 95), gca=95.5 gca peak = 0.11941 (89) mri peak = 0.06553 (92) Left_VentralDC (28): linear fit = 1.12 x + 0.0 (496 voxels, overlap=0.662) Left_VentralDC (28): linear fit = 1.12 x + 0.0 (496 voxels, peak = 100), gca=100.1 gca peak = 0.20775 (25) mri peak = 0.16728 (34) gca peak = 0.13297 (21) mri peak = 0.08047 (23) Fourth_Ventricle (15): linear fit = 1.65 x + 0.0 (296 voxels, overlap=0.400) Fourth_Ventricle (15): linear fit = 1.65 x + 0.0 (296 voxels, peak = 35), gca=34.8 gca peak Unknown = 0.94777 ( 0) gca peak Left_Inf_Lat_Vent = 0.19087 (28) gca peak Third_Ventricle = 0.20775 (25) gca peak Fourth_Ventricle = 0.13297 (21) gca peak CSF = 0.16821 (33) gca peak Left_Accumbens_area = 0.32850 (63) gca peak Left_undetermined = 0.98480 (28) gca peak Left_vessel = 0.40887 (53) gca peak Left_choroid_plexus = 0.10898 (46) gca peak Right_Inf_Lat_Vent = 0.17798 (26) gca peak Right_Accumbens_area = 0.30137 (64) gca peak Right_vessel = 0.47828 (52) gca peak Right_choroid_plexus = 0.11612 (45) gca peak Fifth_Ventricle = 0.59466 (35) gca peak WM_hypointensities = 0.10053 (78) gca peak non_WM_hypointensities = 0.07253 (60) gca peak Optic_Chiasm = 0.25330 (73) not using caudate to estimate GM means estimating mean gm scale to be 1.30 x + 0.0 estimating mean wm scale to be 1.00 x + 0.0 estimating mean csf scale to be 1.50 x + 0.0 Right_Pallidum too bright - rescaling by 0.973 (from 1.065) to 99.4 (was 102.2) saving intensity scales to talairach.label_intensities.txt GCAmapRenormalizeWithAlignment() took 3.6796 min noneg pre Starting GCAMregister() label assignment complete, 0 changed (0.00%) npasses = 1, nlevels = 6 #pass# 1 of 1 ************************ enabling zero nodes setting smoothness cost coefficient to 0.008 #GCAMreg# pass 0 level1 5 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.01 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=256, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.842361 #FOTS# QuadFit found better minimum quadopt=(dt=221.952,rms=0.761558) vs oldopt=(dt=369.92,rms=0.784234) #GCMRL# 102 dt 221.952000 rms 0.762 9.592% neg 0 invalid 762 tFOTS 6.5380 tGradient 2.7020 tsec 9.7160 #FOTS# QuadFit found better minimum quadopt=(dt=352.286,rms=0.740394) vs oldopt=(dt=369.92,rms=0.740459) #GCMRL# 103 dt 352.286079 rms 0.740 2.779% neg 0 invalid 762 tFOTS 6.5740 tGradient 2.8610 tsec 9.9220 #FOTS# QuadFit found better minimum quadopt=(dt=221.952,rms=0.734174) vs oldopt=(dt=369.92,rms=0.735724) #GCMRL# 104 dt 221.952000 rms 0.734 0.840% neg 0 invalid 762 tFOTS 6.1830 tGradient 2.7530 tsec 9.4260 #FOTS# QuadFit found better minimum quadopt=(dt=517.888,rms=0.726761) vs oldopt=(dt=369.92,rms=0.727833) #GCMRL# 105 dt 517.888000 rms 0.727 1.010% neg 0 invalid 762 tFOTS 6.5200 tGradient 2.8590 tsec 9.8700 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.724517) vs oldopt=(dt=92.48,rms=0.724924) #GCMRL# 106 dt 129.472000 rms 0.725 0.309% neg 0 invalid 762 tFOTS 6.4510 tGradient 2.6610 tsec 9.6070 #FOTS# QuadFit found better minimum quadopt=(dt=517.888,rms=0.72137) vs oldopt=(dt=369.92,rms=0.721966) #GCMRL# 107 dt 517.888000 rms 0.721 0.434% neg 0 invalid 762 tFOTS 6.5930 tGradient 2.7560 tsec 9.8330 #GCMRL# 108 dt 369.920000 rms 0.719 0.318% neg 0 invalid 762 tFOTS 6.5110 tGradient 2.7230 tsec 9.7170 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.717948) vs oldopt=(dt=92.48,rms=0.718089) #GCMRL# 109 dt 129.472000 rms 0.718 0.156% neg 0 invalid 762 tFOTS 6.5130 tGradient 2.7780 tsec 9.7700 #GCMRL# 110 dt 1479.680000 rms 0.715 0.437% neg 0 invalid 762 tFOTS 6.7060 tGradient 2.9490 tsec 10.1640 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.713196) vs oldopt=(dt=92.48,rms=0.713518) #GCMRL# 111 dt 129.472000 rms 0.713 0.226% neg 0 invalid 762 tFOTS 6.5280 tGradient 2.9230 tsec 9.8490 #FOTS# QuadFit found better minimum quadopt=(dt=517.888,rms=0.711777) vs oldopt=(dt=369.92,rms=0.712054) #GCMRL# 112 dt 517.888000 rms 0.712 0.199% neg 0 invalid 762 tFOTS 7.0950 tGradient 2.8610 tsec 10.4520 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.711453) vs oldopt=(dt=92.48,rms=0.711489) #GCMRL# 113 dt 129.472000 rms 0.711 0.000% neg 0 invalid 762 tFOTS 6.6170 tGradient 2.6600 tsec 9.7380 #GCMRL# 114 dt 129.472000 rms 0.711 0.031% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8380 tsec 3.3340 #GCMRL# 115 dt 129.472000 rms 0.711 0.062% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6910 tsec 3.2060 #GCMRL# 116 dt 129.472000 rms 0.710 0.089% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6860 tsec 3.1820 #GCMRL# 117 dt 129.472000 rms 0.709 0.112% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8110 tsec 3.3170 #GCMRL# 118 dt 129.472000 rms 0.708 0.128% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.9890 tsec 3.4880 #GCMRL# 119 dt 129.472000 rms 0.707 0.137% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8950 tsec 3.3810 #GCMRL# 120 dt 129.472000 rms 0.707 0.128% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.0430 tsec 3.5450 #GCMRL# 121 dt 129.472000 rms 0.706 0.132% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6950 tsec 3.1360 #GCMRL# 122 dt 129.472000 rms 0.705 0.135% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7430 tsec 3.2290 #GCMRL# 123 dt 129.472000 rms 0.704 0.137% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8990 tsec 3.3960 #GCMRL# 124 dt 129.472000 rms 0.703 0.119% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8580 tsec 3.3620 #GCMRL# 125 dt 129.472000 rms 0.702 0.116% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7880 tsec 3.2810 #GCMRL# 126 dt 129.472000 rms 0.701 0.114% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.0160 tsec 3.5280 #GCMRL# 127 dt 129.472000 rms 0.701 0.104% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7650 tsec 3.2660 #GCMRL# 128 dt 129.472000 rms 0.700 0.101% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5030 tsec 3.0050 #GCMRL# 129 dt 129.472000 rms 0.699 0.105% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7880 tsec 3.2860 #GCMRL# 130 dt 129.472000 rms 0.698 0.105% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7320 tsec 3.2390 #GCMRL# 131 dt 129.472000 rms 0.698 0.105% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7290 tsec 3.2260 #GCMRL# 132 dt 129.472000 rms 0.697 0.103% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6530 tsec 3.1500 #GCMRL# 133 dt 129.472000 rms 0.696 0.106% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5730 tsec 3.0830 #GCMRL# 134 dt 129.472000 rms 0.696 0.095% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7800 tsec 3.2650 #GCMRL# 135 dt 129.472000 rms 0.695 0.093% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6630 tsec 3.1560 #GCMRL# 136 dt 129.472000 rms 0.694 0.091% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6490 tsec 3.1500 #GCMRL# 137 dt 129.472000 rms 0.694 0.082% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6360 tsec 3.1350 #GCMRL# 138 dt 129.472000 rms 0.693 0.077% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6190 tsec 3.1220 #GCMRL# 139 dt 129.472000 rms 0.693 0.084% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7990 tsec 3.2990 #GCMRL# 140 dt 129.472000 rms 0.692 0.072% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5460 tsec 3.0400 #GCMRL# 141 dt 129.472000 rms 0.692 0.072% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7530 tsec 3.2670 #GCMRL# 142 dt 129.472000 rms 0.691 0.065% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7640 tsec 3.2590 #GCMRL# 143 dt 129.472000 rms 0.691 0.063% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6180 tsec 3.1140 #GCMRL# 144 dt 129.472000 rms 0.690 0.059% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7970 tsec 3.2830 #GCMRL# 145 dt 129.472000 rms 0.690 0.060% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6740 tsec 3.1590 #GCMRL# 146 dt 129.472000 rms 0.689 0.062% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8810 tsec 3.4000 #GCMRL# 147 dt 129.472000 rms 0.689 0.060% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6600 tsec 3.1500 #GCMRL# 148 dt 129.472000 rms 0.689 0.062% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8010 tsec 3.2920 #GCMRL# 149 dt 129.472000 rms 0.688 0.066% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8740 tsec 3.3720 #GCMRL# 150 dt 129.472000 rms 0.688 0.069% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5870 tsec 3.0920 #GCMRL# 151 dt 129.472000 rms 0.687 0.066% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8210 tsec 3.3310 #GCMRL# 152 dt 129.472000 rms 0.687 0.067% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6380 tsec 3.1360 #GCMRL# 153 dt 129.472000 rms 0.686 0.060% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5840 tsec 3.0820 #GCMRL# 154 dt 129.472000 rms 0.686 0.055% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7810 tsec 3.3080 #GCMRL# 155 dt 129.472000 rms 0.686 0.052% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7500 tsec 3.2570 #GCMRL# 156 dt 129.472000 rms 0.685 0.049% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7830 tsec 3.2980 #GCMRL# 157 dt 129.472000 rms 0.685 0.050% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5160 tsec 3.0110 #GCMRL# 158 dt 129.472000 rms 0.685 0.049% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7070 tsec 3.2110 #GCMRL# 159 dt 129.472000 rms 0.684 0.050% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8500 tsec 3.3470 #GCMRL# 160 dt 129.472000 rms 0.684 0.044% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5610 tsec 3.0660 #GCMRL# 161 dt 129.472000 rms 0.684 0.042% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.9800 tsec 3.4750 #GCMRL# 162 dt 129.472000 rms 0.683 0.041% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7170 tsec 3.2240 #GCMRL# 163 dt 129.472000 rms 0.683 0.038% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7680 tsec 3.2640 #GCMRL# 164 dt 129.472000 rms 0.683 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8570 tsec 3.3530 #GCMRL# 165 dt 129.472000 rms 0.683 0.036% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.0000 tsec 3.5010 #GCMRL# 166 dt 129.472000 rms 0.682 0.035% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6950 tsec 3.2010 #GCMRL# 167 dt 129.472000 rms 0.682 0.035% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6630 tsec 3.1590 #GCMRL# 168 dt 129.472000 rms 0.682 0.032% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6230 tsec 3.1220 #GCMRL# 169 dt 129.472000 rms 0.682 0.029% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7810 tsec 3.2840 #GCMRL# 170 dt 129.472000 rms 0.682 0.026% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7790 tsec 3.2840 #GCMRL# 171 dt 129.472000 rms 0.681 0.024% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6500 tsec 3.1490 #GCMRL# 172 dt 129.472000 rms 0.681 0.026% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6430 tsec 3.1420 #GCMRL# 173 dt 129.472000 rms 0.681 0.031% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6320 tsec 3.1340 #GCMRL# 174 dt 129.472000 rms 0.681 0.030% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7150 tsec 3.2120 #GCMRL# 175 dt 129.472000 rms 0.681 0.031% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6800 tsec 3.1710 #GCMRL# 176 dt 129.472000 rms 0.680 0.029% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.4860 tsec 2.9640 #GCMRL# 177 dt 129.472000 rms 0.680 0.032% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6740 tsec 3.1750 #GCMRL# 178 dt 129.472000 rms 0.680 0.029% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.4530 tsec 2.9560 #GCMRL# 179 dt 129.472000 rms 0.680 0.031% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7570 tsec 3.2610 #GCMRL# 180 dt 129.472000 rms 0.680 0.029% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.4540 tsec 2.9510 #GCMRL# 181 dt 129.472000 rms 0.679 0.027% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6100 tsec 3.1210 #GCMRL# 182 dt 129.472000 rms 0.679 0.029% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5850 tsec 3.0920 #GCMRL# 183 dt 129.472000 rms 0.679 0.026% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8650 tsec 3.3740 #GCMRL# 184 dt 129.472000 rms 0.679 0.024% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6830 tsec 3.1780 #GCMRL# 185 dt 129.472000 rms 0.679 0.024% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6770 tsec 3.1770 #GCMRL# 186 dt 129.472000 rms 0.678 0.023% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5780 tsec 3.0990 #FOTS# QuadFit found better minimum quadopt=(dt=2071.55,rms=0.678151) vs oldopt=(dt=1479.68,rms=0.678216) #GCMRL# 187 dt 2071.552000 rms 0.678 0.050% neg 0 invalid 762 tFOTS 6.9140 tGradient 2.6910 tsec 10.0860 #FOTS# QuadFit found better minimum quadopt=(dt=110.976,rms=0.67811) vs oldopt=(dt=92.48,rms=0.678111) #GCMRL# 188 dt 110.976000 rms 0.678 0.000% neg 0 invalid 762 tFOTS 6.9560 tGradient 2.7150 tsec 10.1720 #GCMRL# 189 dt 110.976000 rms 0.678 0.002% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5030 tsec 2.9990 #GCAMreg# pass 0 level1 5 level2 1 tsec 383.284 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.01 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=256, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.678376 #FOTS# QuadFit found better minimum quadopt=(dt=221.952,rms=0.677144) vs oldopt=(dt=369.92,rms=0.677364) #GCMRL# 191 dt 221.952000 rms 0.677 0.182% neg 0 invalid 762 tFOTS 6.5490 tGradient 2.7000 tsec 9.7190 #FOTS# QuadFit found better minimum quadopt=(dt=1183.74,rms=0.675499) vs oldopt=(dt=1479.68,rms=0.675724) #GCMRL# 192 dt 1183.744000 rms 0.675 0.243% neg 0 invalid 762 tFOTS 7.0360 tGradient 2.7220 tsec 10.2260 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.675101) vs oldopt=(dt=92.48,rms=0.675178) #GCMRL# 193 dt 129.472000 rms 0.675 0.059% neg 0 invalid 762 tFOTS 6.5690 tGradient 2.7570 tsec 9.8010 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.67496) vs oldopt=(dt=92.48,rms=0.674975) #GCMRL# 194 dt 129.472000 rms 0.675 0.000% neg 0 invalid 762 tFOTS 7.0170 tGradient 2.7460 tsec 10.2420 #GCMRL# 195 dt 129.472000 rms 0.675 0.013% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7790 tsec 3.2800 #GCMRL# 196 dt 129.472000 rms 0.675 0.016% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6260 tsec 3.1130 #GCMRL# 197 dt 129.472000 rms 0.675 0.019% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5850 tsec 3.0920 #GCMRL# 198 dt 129.472000 rms 0.674 0.030% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7150 tsec 3.2200 #GCMRL# 199 dt 129.472000 rms 0.674 0.043% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8010 tsec 3.2900 #GCMRL# 200 dt 129.472000 rms 0.674 0.050% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8130 tsec 3.3120 #GCMRL# 201 dt 129.472000 rms 0.673 0.056% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7510 tsec 3.2520 #GCMRL# 202 dt 129.472000 rms 0.673 0.050% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6350 tsec 3.1350 #GCMRL# 203 dt 129.472000 rms 0.673 0.039% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8150 tsec 3.3180 #GCMRL# 204 dt 129.472000 rms 0.673 0.038% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7220 tsec 3.2130 #GCMRL# 205 dt 129.472000 rms 0.672 0.028% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6130 tsec 3.1170 #GCMRL# 206 dt 129.472000 rms 0.672 0.024% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5130 tsec 2.9710 #GCMRL# 207 dt 129.472000 rms 0.672 0.017% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6460 tsec 3.1610 #FOTS# QuadFit found better minimum quadopt=(dt=1183.74,rms=0.671915) vs oldopt=(dt=1479.68,rms=0.67195) #GCMRL# 208 dt 1183.744000 rms 0.672 0.031% neg 0 invalid 762 tFOTS 6.5830 tGradient 2.7360 tsec 9.7920 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.671832) vs oldopt=(dt=92.48,rms=0.671853) #GCMRL# 209 dt 129.472000 rms 0.672 0.000% neg 0 invalid 762 tFOTS 6.7610 tGradient 2.6930 tsec 9.9690 #GCMRL# 210 dt 129.472000 rms 0.672 0.007% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6090 tsec 3.1050 #GCMRL# 211 dt 129.472000 rms 0.672 0.004% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7230 tsec 3.2190 setting smoothness cost coefficient to 0.031 #GCAMreg# pass 0 level1 4 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.03 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=64, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.674419 #FOTS# QuadFit found better minimum quadopt=(dt=82.944,rms=0.672631) vs oldopt=(dt=103.68,rms=0.672765) #GCMRL# 213 dt 82.944000 rms 0.673 0.265% neg 0 invalid 762 tFOTS 6.3900 tGradient 2.3230 tsec 9.1890 #FOTS# QuadFit found better minimum quadopt=(dt=331.776,rms=0.667681) vs oldopt=(dt=414.72,rms=0.667785) #GCMRL# 214 dt 331.776000 rms 0.668 0.736% neg 0 invalid 762 tFOTS 6.0010 tGradient 2.2070 tsec 8.6930 #FOTS# QuadFit found better minimum quadopt=(dt=145.152,rms=0.663826) vs oldopt=(dt=103.68,rms=0.664098) #GCMRL# 215 dt 145.152000 rms 0.664 0.577% neg 0 invalid 762 tFOTS 6.4650 tGradient 2.2880 tsec 9.2430 #FOTS# QuadFit found better minimum quadopt=(dt=102.945,rms=0.661235) vs oldopt=(dt=103.68,rms=0.661236) #GCMRL# 216 dt 102.944681 rms 0.661 0.390% neg 0 invalid 762 tFOTS 6.7050 tGradient 2.0620 tsec 9.2500 #FOTS# QuadFit found better minimum quadopt=(dt=124.416,rms=0.659653) vs oldopt=(dt=103.68,rms=0.659688) #GCMRL# 217 dt 124.416000 rms 0.660 0.239% neg 0 invalid 762 tFOTS 6.0190 tGradient 2.2130 tsec 8.7160 #FOTS# QuadFit found better minimum quadopt=(dt=145.152,rms=0.657806) vs oldopt=(dt=103.68,rms=0.657892) #GCMRL# 218 dt 145.152000 rms 0.658 0.280% neg 0 invalid 762 tFOTS 6.4960 tGradient 2.0400 tsec 9.0180 #FOTS# QuadFit found better minimum quadopt=(dt=81.8739,rms=0.65637) vs oldopt=(dt=103.68,rms=0.65648) #GCMRL# 219 dt 81.873874 rms 0.656 0.218% neg 0 invalid 762 tFOTS 6.4610 tGradient 2.1630 tsec 9.1460 #FOTS# QuadFit found better minimum quadopt=(dt=248.832,rms=0.654157) vs oldopt=(dt=414.72,rms=0.654921) #GCMRL# 220 dt 248.832000 rms 0.654 0.337% neg 0 invalid 762 tFOTS 6.4070 tGradient 2.1630 tsec 9.0580 #FOTS# QuadFit found better minimum quadopt=(dt=71.4232,rms=0.652759) vs oldopt=(dt=103.68,rms=0.653065) #GCMRL# 221 dt 71.423197 rms 0.653 0.214% neg 0 invalid 762 tFOTS 6.5380 tGradient 2.1340 tsec 9.1640 #GCMRL# 222 dt 414.720000 rms 0.651 0.329% neg 0 invalid 762 tFOTS 6.4420 tGradient 2.1120 tsec 9.0430 #FOTS# QuadFit found better minimum quadopt=(dt=36.288,rms=0.64908) vs oldopt=(dt=25.92,rms=0.649409) #GCMRL# 223 dt 36.288000 rms 0.649 0.236% neg 0 invalid 762 tFOTS 6.2990 tGradient 2.0860 tsec 8.8590 #GCMRL# 224 dt 103.680000 rms 0.648 0.136% neg 0 invalid 762 tFOTS 6.4680 tGradient 2.2440 tsec 9.1960 #FOTS# QuadFit found better minimum quadopt=(dt=124.416,rms=0.647388) vs oldopt=(dt=103.68,rms=0.647417) #GCMRL# 225 dt 124.416000 rms 0.647 0.125% neg 0 invalid 762 tFOTS 6.4360 tGradient 1.9990 tsec 8.9470 #GCMRL# 226 dt 103.680000 rms 0.647 0.104% neg 0 invalid 762 tFOTS 6.4220 tGradient 2.1850 tsec 9.0980 #FOTS# QuadFit found better minimum quadopt=(dt=124.416,rms=0.645977) vs oldopt=(dt=103.68,rms=0.645994) #GCMRL# 227 dt 124.416000 rms 0.646 0.114% neg 0 invalid 762 tFOTS 6.3690 tGradient 2.3230 tsec 9.1630 #FOTS# QuadFit found better minimum quadopt=(dt=82.944,rms=0.645345) vs oldopt=(dt=103.68,rms=0.645353) #GCMRL# 228 dt 82.944000 rms 0.645 0.098% neg 0 invalid 762 tFOTS 6.4430 tGradient 2.1880 tsec 9.0920 #FOTS# QuadFit found better minimum quadopt=(dt=145.152,rms=0.644491) vs oldopt=(dt=103.68,rms=0.644651) #GCMRL# 229 dt 145.152000 rms 0.644 0.132% neg 0 invalid 762 tFOTS 6.3190 tGradient 2.1350 tsec 8.9490 #GCMRL# 230 dt 103.680000 rms 0.644 0.079% neg 0 invalid 762 tFOTS 6.3880 tGradient 2.0460 tsec 8.9210 #FOTS# QuadFit found better minimum quadopt=(dt=124.416,rms=0.643291) vs oldopt=(dt=103.68,rms=0.643314) #GCMRL# 231 dt 124.416000 rms 0.643 0.107% neg 0 invalid 762 tFOTS 6.4210 tGradient 2.1750 tsec 9.0840 #FOTS# QuadFit found better minimum quadopt=(dt=82.944,rms=0.642893) vs oldopt=(dt=103.68,rms=0.642955) #GCMRL# 232 dt 82.944000 rms 0.643 0.062% neg 0 invalid 762 tFOTS 6.3970 tGradient 2.1860 tsec 9.0590 #FOTS# QuadFit found better minimum quadopt=(dt=145.152,rms=0.641987) vs oldopt=(dt=103.68,rms=0.642137) #GCMRL# 233 dt 145.152000 rms 0.642 0.141% neg 0 invalid 762 tFOTS 6.6520 tGradient 2.0960 tsec 9.2270 #FOTS# QuadFit found better minimum quadopt=(dt=62.208,rms=0.64166) vs oldopt=(dt=103.68,rms=0.641785) #GCMRL# 234 dt 62.208000 rms 0.642 0.051% neg 0 invalid 762 tFOTS 6.5780 tGradient 2.1660 tsec 9.2440 #FOTS# QuadFit found better minimum quadopt=(dt=580.608,rms=0.639619) vs oldopt=(dt=414.72,rms=0.639948) #GCMRL# 235 dt 580.608000 rms 0.640 0.318% neg 0 invalid 762 tFOTS 6.3060 tGradient 2.0770 tsec 8.8700 #FOTS# QuadFit found better minimum quadopt=(dt=36.288,rms=0.638716) vs oldopt=(dt=25.92,rms=0.638877) #GCMRL# 236 dt 36.288000 rms 0.639 0.141% neg 0 invalid 762 tFOTS 6.4490 tGradient 2.1310 tsec 9.0480 #FOTS# QuadFit found better minimum quadopt=(dt=62.208,rms=0.638496) vs oldopt=(dt=103.68,rms=0.638534) #GCMRL# 237 dt 62.208000 rms 0.638 0.000% neg 0 invalid 762 tFOTS 6.4900 tGradient 2.1610 tsec 9.1440 #GCMRL# 238 dt 62.208000 rms 0.638 0.049% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2050 tsec 2.7110 #GCMRL# 239 dt 62.208000 rms 0.638 0.078% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0400 tsec 2.5310 #GCMRL# 240 dt 62.208000 rms 0.637 0.105% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1320 tsec 2.5860 #GCMRL# 241 dt 62.208000 rms 0.636 0.123% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1600 tsec 2.6550 #GCMRL# 242 dt 62.208000 rms 0.635 0.151% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1280 tsec 2.6260 #GCMRL# 243 dt 62.208000 rms 0.634 0.162% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2080 tsec 2.6730 #GCMRL# 244 dt 62.208000 rms 0.633 0.156% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0560 tsec 2.5330 #GCMRL# 245 dt 62.208000 rms 0.632 0.142% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2570 tsec 2.7640 #GCMRL# 246 dt 62.208000 rms 0.631 0.138% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1130 tsec 2.6050 #GCMRL# 247 dt 62.208000 rms 0.631 0.140% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1520 tsec 2.6400 #GCMRL# 248 dt 62.208000 rms 0.630 0.137% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1600 tsec 2.6580 #GCMRL# 249 dt 62.208000 rms 0.629 0.122% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0280 tsec 2.5270 #GCMRL# 250 dt 62.208000 rms 0.628 0.138% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2090 tsec 2.6990 #GCMRL# 251 dt 62.208000 rms 0.627 0.110% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.3140 tsec 2.8170 #GCMRL# 252 dt 62.208000 rms 0.627 0.105% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1380 tsec 2.6380 #GCMRL# 253 dt 62.208000 rms 0.626 0.112% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2000 tsec 2.6590 #GCMRL# 254 dt 62.208000 rms 0.625 0.116% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1910 tsec 2.6940 #GCMRL# 255 dt 62.208000 rms 0.625 0.110% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1980 tsec 2.6780 #GCMRL# 256 dt 62.208000 rms 0.624 0.099% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1600 tsec 2.6510 #GCMRL# 257 dt 62.208000 rms 0.623 0.093% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1480 tsec 2.6450 #GCMRL# 258 dt 62.208000 rms 0.623 0.106% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1260 tsec 2.6140 #GCMRL# 259 dt 62.208000 rms 0.622 0.097% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1690 tsec 2.6640 #GCMRL# 260 dt 62.208000 rms 0.622 0.097% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2540 tsec 2.7120 #GCMRL# 261 dt 62.208000 rms 0.621 0.089% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1610 tsec 2.6550 #GCMRL# 262 dt 62.208000 rms 0.621 0.075% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1460 tsec 2.6320 #GCMRL# 263 dt 62.208000 rms 0.620 0.079% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1280 tsec 2.6160 #GCMRL# 264 dt 62.208000 rms 0.620 0.080% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1600 tsec 2.6550 #GCMRL# 265 dt 62.208000 rms 0.619 0.068% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9920 tsec 2.5000 #GCMRL# 266 dt 62.208000 rms 0.619 0.064% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1480 tsec 2.6370 #GCMRL# 267 dt 62.208000 rms 0.618 0.066% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2170 tsec 2.7110 #GCMRL# 268 dt 62.208000 rms 0.618 0.066% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2420 tsec 2.7440 #GCMRL# 269 dt 62.208000 rms 0.618 0.062% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2460 tsec 2.7360 #GCMRL# 270 dt 62.208000 rms 0.617 0.057% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2020 tsec 2.6950 #GCMRL# 271 dt 62.208000 rms 0.617 0.053% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2820 tsec 2.7810 #GCMRL# 272 dt 62.208000 rms 0.617 0.043% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1910 tsec 2.6750 #GCMRL# 273 dt 62.208000 rms 0.616 0.044% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1900 tsec 2.6630 #GCMRL# 274 dt 62.208000 rms 0.616 0.038% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2830 tsec 2.7760 #GCMRL# 275 dt 62.208000 rms 0.616 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1960 tsec 2.6870 #GCMRL# 276 dt 62.208000 rms 0.616 0.040% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1490 tsec 2.6210 #GCMRL# 277 dt 62.208000 rms 0.615 0.042% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1690 tsec 2.6590 #GCMRL# 278 dt 62.208000 rms 0.615 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2110 tsec 2.7170 #GCMRL# 279 dt 62.208000 rms 0.615 0.036% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1450 tsec 2.6230 #GCMRL# 280 dt 62.208000 rms 0.615 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1400 tsec 2.6310 #GCMRL# 281 dt 62.208000 rms 0.614 0.044% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2190 tsec 2.7080 #GCMRL# 282 dt 62.208000 rms 0.614 0.041% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0980 tsec 2.5780 #GCMRL# 283 dt 62.208000 rms 0.614 0.047% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1390 tsec 2.6330 #GCMRL# 284 dt 62.208000 rms 0.614 0.043% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1390 tsec 2.6450 #GCMRL# 285 dt 62.208000 rms 0.613 0.040% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1420 tsec 2.6420 #GCMRL# 286 dt 62.208000 rms 0.613 0.030% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1840 tsec 2.6800 #GCMRL# 287 dt 62.208000 rms 0.613 0.023% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1130 tsec 2.6140 #GCMRL# 288 dt 62.208000 rms 0.613 0.025% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1110 tsec 2.5990 #GCMRL# 289 dt 62.208000 rms 0.613 0.030% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2170 tsec 2.7070 #GCMRL# 290 dt 62.208000 rms 0.612 0.035% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0640 tsec 2.5380 #GCMRL# 291 dt 62.208000 rms 0.612 0.041% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1740 tsec 2.6730 #GCMRL# 292 dt 62.208000 rms 0.612 0.020% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1200 tsec 2.6220 #GCMRL# 293 dt 62.208000 rms 0.612 0.027% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2100 tsec 2.7290 #GCMRL# 294 dt 62.208000 rms 0.612 0.024% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1870 tsec 2.6780 #GCMRL# 295 dt 62.208000 rms 0.612 0.020% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2340 tsec 2.7500 #FOTS# QuadFit found better minimum quadopt=(dt=145.152,rms=0.61155) vs oldopt=(dt=103.68,rms=0.611554) #GCMRL# 296 dt 145.152000 rms 0.612 0.000% neg 0 invalid 762 tFOTS 6.5040 tGradient 2.1170 tsec 9.1370 #GCAMreg# pass 0 level1 4 level2 1 tsec 395.86 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.03 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=64, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.611921 #FOTS# QuadFit found better minimum quadopt=(dt=145.152,rms=0.608762) vs oldopt=(dt=103.68,rms=0.60897) #GCMRL# 298 dt 145.152000 rms 0.609 0.516% neg 0 invalid 762 tFOTS 6.3990 tGradient 2.3030 tsec 9.1890 #FOTS# QuadFit found better minimum quadopt=(dt=36.288,rms=0.608088) vs oldopt=(dt=25.92,rms=0.608207) #GCMRL# 299 dt 36.288000 rms 0.608 0.111% neg 0 invalid 762 tFOTS 6.3430 tGradient 2.2300 tsec 9.0550 #FOTS# QuadFit found better minimum quadopt=(dt=145.152,rms=0.607265) vs oldopt=(dt=103.68,rms=0.607403) #GCMRL# 300 dt 145.152000 rms 0.607 0.135% neg 0 invalid 762 tFOTS 6.3790 tGradient 2.1050 tsec 8.9630 #FOTS# QuadFit found better minimum quadopt=(dt=124.416,rms=0.606859) vs oldopt=(dt=103.68,rms=0.60686) #GCMRL# 301 dt 124.416000 rms 0.607 0.067% neg 0 invalid 762 tFOTS 6.1100 tGradient 2.1380 tsec 8.7430 #GCMRL# 302 dt 103.680000 rms 0.607 0.057% neg 0 invalid 762 tFOTS 6.4220 tGradient 2.1110 tsec 9.0240 #GCMRL# 303 dt 103.680000 rms 0.606 0.066% neg 0 invalid 762 tFOTS 6.3670 tGradient 2.2040 tsec 9.0590 #FOTS# QuadFit found better minimum quadopt=(dt=36.288,rms=0.60599) vs oldopt=(dt=25.92,rms=0.606) #GCMRL# 304 dt 36.288000 rms 0.606 0.000% neg 0 invalid 762 tFOTS 6.7820 tGradient 2.1070 tsec 9.3790 #GCMRL# 305 dt 36.288000 rms 0.606 0.012% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2150 tsec 2.6980 #GCMRL# 306 dt 36.288000 rms 0.606 0.025% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1480 tsec 2.6400 #GCMRL# 307 dt 36.288000 rms 0.606 0.035% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1170 tsec 2.6050 #GCMRL# 308 dt 36.288000 rms 0.605 0.045% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1510 tsec 2.6420 #GCMRL# 309 dt 36.288000 rms 0.605 0.047% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1390 tsec 2.6280 #GCMRL# 310 dt 36.288000 rms 0.605 0.052% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1540 tsec 2.6450 #GCMRL# 311 dt 36.288000 rms 0.604 0.049% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1480 tsec 2.6440 #GCMRL# 312 dt 36.288000 rms 0.604 0.049% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1390 tsec 2.6300 #GCMRL# 313 dt 36.288000 rms 0.604 0.051% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2560 tsec 2.7490 #GCMRL# 314 dt 36.288000 rms 0.603 0.055% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1050 tsec 2.6040 #GCMRL# 315 dt 36.288000 rms 0.603 0.057% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1120 tsec 2.6120 #GCMRL# 316 dt 36.288000 rms 0.603 0.057% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2000 tsec 2.6640 #GCMRL# 317 dt 36.288000 rms 0.602 0.055% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2700 tsec 2.7700 #GCMRL# 318 dt 36.288000 rms 0.602 0.047% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1990 tsec 2.6880 #GCMRL# 319 dt 36.288000 rms 0.602 0.045% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2080 tsec 2.6990 #GCMRL# 320 dt 36.288000 rms 0.602 0.038% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2430 tsec 2.7330 #GCMRL# 321 dt 36.288000 rms 0.601 0.038% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0550 tsec 2.5420 #GCMRL# 322 dt 36.288000 rms 0.601 0.031% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2200 tsec 2.7250 #GCMRL# 323 dt 36.288000 rms 0.601 0.029% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1960 tsec 2.6860 #GCMRL# 324 dt 36.288000 rms 0.601 0.033% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1190 tsec 2.6280 #GCMRL# 325 dt 36.288000 rms 0.601 0.032% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1640 tsec 2.6300 #GCMRL# 326 dt 36.288000 rms 0.600 0.033% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0350 tsec 2.5270 #GCMRL# 327 dt 36.288000 rms 0.600 0.035% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1980 tsec 2.6860 #GCMRL# 328 dt 36.288000 rms 0.600 0.038% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2760 tsec 2.7590 #GCMRL# 329 dt 36.288000 rms 0.600 0.036% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1990 tsec 2.6820 #GCMRL# 330 dt 36.288000 rms 0.600 0.028% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1520 tsec 2.6440 #GCMRL# 331 dt 36.288000 rms 0.599 0.029% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2000 tsec 2.6830 #GCMRL# 332 dt 36.288000 rms 0.599 0.024% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1520 tsec 2.6380 #GCMRL# 333 dt 36.288000 rms 0.599 0.022% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1840 tsec 2.6840 #FOTS# QuadFit found better minimum quadopt=(dt=145.152,rms=0.599082) vs oldopt=(dt=103.68,rms=0.599109) #GCMRL# 334 dt 145.152000 rms 0.599 0.000% neg 0 invalid 762 tFOTS 6.3590 tGradient 2.2250 tsec 9.0920 setting smoothness cost coefficient to 0.118 #GCAMreg# pass 0 level1 3 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.12 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=16, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.611937 #FOTS# QuadFit found better minimum quadopt=(dt=11.2,rms=0.611105) vs oldopt=(dt=8,rms=0.61118) #GCMRL# 336 dt 11.200000 rms 0.611 0.136% neg 0 invalid 762 tFOTS 6.5260 tGradient 1.9480 tsec 8.9680 #FOTS# QuadFit found better minimum quadopt=(dt=11.2,rms=0.610782) vs oldopt=(dt=8,rms=0.610837) #GCMRL# 337 dt 11.200000 rms 0.611 0.053% neg 0 invalid 762 tFOTS 6.4260 tGradient 2.0680 tsec 8.9800 #FOTS# QuadFit found better minimum quadopt=(dt=11.2,rms=0.610538) vs oldopt=(dt=8,rms=0.610593) #GCMRL# 338 dt 11.200000 rms 0.611 0.000% neg 0 invalid 762 tFOTS 6.4660 tGradient 2.1950 tsec 9.1760 #GCMRL# 339 dt 11.200000 rms 0.610 0.043% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2100 tsec 2.7040 #GCMRL# 340 dt 11.200000 rms 0.610 0.042% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8880 tsec 2.3870 #GCMRL# 341 dt 11.200000 rms 0.610 0.026% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9500 tsec 2.4190 #GCMRL# 342 dt 11.200000 rms 0.610 0.057% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9880 tsec 2.4880 #GCMRL# 343 dt 11.200000 rms 0.609 0.111% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9220 tsec 2.4150 #GCMRL# 344 dt 11.200000 rms 0.608 0.187% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0540 tsec 2.5520 #GCMRL# 345 dt 11.200000 rms 0.606 0.255% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9500 tsec 2.4480 #GCMRL# 346 dt 11.200000 rms 0.604 0.307% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9940 tsec 2.4810 #GCMRL# 347 dt 11.200000 rms 0.602 0.322% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9750 tsec 2.4640 #GCMRL# 348 dt 11.200000 rms 0.600 0.312% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0070 tsec 2.4870 #GCMRL# 349 dt 11.200000 rms 0.599 0.309% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9600 tsec 2.4510 #GCMRL# 350 dt 11.200000 rms 0.597 0.304% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9310 tsec 2.4290 #GCMRL# 351 dt 11.200000 rms 0.595 0.290% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0080 tsec 2.5040 #GCMRL# 352 dt 11.200000 rms 0.593 0.262% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0190 tsec 2.5140 #GCMRL# 353 dt 11.200000 rms 0.592 0.230% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9660 tsec 2.4740 #GCMRL# 354 dt 11.200000 rms 0.591 0.215% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0960 tsec 2.5890 #GCMRL# 355 dt 11.200000 rms 0.590 0.186% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8550 tsec 2.3530 #GCMRL# 356 dt 11.200000 rms 0.589 0.181% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0930 tsec 2.5780 #GCMRL# 357 dt 11.200000 rms 0.588 0.172% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0190 tsec 2.5120 #GCMRL# 358 dt 11.200000 rms 0.587 0.160% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0750 tsec 2.5710 #GCMRL# 359 dt 11.200000 rms 0.586 0.150% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9910 tsec 2.4850 #GCMRL# 360 dt 11.200000 rms 0.585 0.133% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0140 tsec 2.5060 #GCMRL# 361 dt 11.200000 rms 0.584 0.117% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9920 tsec 2.4830 #GCMRL# 362 dt 11.200000 rms 0.584 0.105% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9260 tsec 2.4280 #GCMRL# 363 dt 11.200000 rms 0.583 0.091% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8740 tsec 2.3620 #GCMRL# 364 dt 11.200000 rms 0.583 0.087% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0460 tsec 2.5320 #GCMRL# 365 dt 11.200000 rms 0.582 0.075% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9960 tsec 2.5010 #GCMRL# 366 dt 11.200000 rms 0.582 0.072% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8710 tsec 2.3700 #GCMRL# 367 dt 11.200000 rms 0.582 0.061% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9090 tsec 2.4070 #GCMRL# 368 dt 11.200000 rms 0.581 0.056% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9780 tsec 2.4720 #GCMRL# 369 dt 11.200000 rms 0.581 0.040% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0480 tsec 2.5090 #GCMRL# 370 dt 11.200000 rms 0.581 0.032% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0100 tsec 2.5070 #GCMRL# 371 dt 11.200000 rms 0.581 0.031% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9760 tsec 2.4620 #GCMRL# 372 dt 11.200000 rms 0.580 0.036% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9240 tsec 2.4180 #GCMRL# 373 dt 11.200000 rms 0.580 0.040% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0510 tsec 2.5470 #GCMRL# 374 dt 11.200000 rms 0.580 0.040% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8580 tsec 2.3510 #GCMRL# 375 dt 11.200000 rms 0.580 0.045% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9960 tsec 2.4920 #GCMRL# 376 dt 11.200000 rms 0.579 0.043% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8880 tsec 2.3870 #GCMRL# 377 dt 11.200000 rms 0.579 0.043% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9750 tsec 2.4760 #GCMRL# 378 dt 11.200000 rms 0.579 0.047% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9670 tsec 2.4690 #GCMRL# 379 dt 11.200000 rms 0.579 0.047% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9220 tsec 2.4160 #GCMRL# 380 dt 11.200000 rms 0.578 0.039% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9870 tsec 2.4820 #GCMRL# 381 dt 11.200000 rms 0.578 0.032% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9330 tsec 2.4320 #GCMRL# 382 dt 11.200000 rms 0.578 0.029% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9270 tsec 2.4110 #GCMRL# 383 dt 11.200000 rms 0.578 0.025% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9790 tsec 2.4710 #GCMRL# 384 dt 11.200000 rms 0.578 0.020% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9750 tsec 2.4900 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.577739) vs oldopt=(dt=32,rms=0.577745) #GCMRL# 385 dt 44.800000 rms 0.578 0.000% neg 0 invalid 762 tFOTS 6.1470 tGradient 2.0140 tsec 8.6720 #GCMRL# 386 dt 44.800000 rms 0.578 0.031% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0710 tsec 2.5200 #GCMRL# 387 dt 44.800000 rms 0.578 0.010% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9230 tsec 2.4180 #GCMRL# 388 dt 44.800000 rms 0.577 0.006% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0810 tsec 2.5910 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.577282) vs oldopt=(dt=32,rms=0.577289) #GCMRL# 389 dt 44.800000 rms 0.577 0.032% neg 0 invalid 762 tFOTS 6.1990 tGradient 1.9760 tsec 8.6530 #FOTS# QuadFit found better minimum quadopt=(dt=11.2,rms=0.577291) vs oldopt=(dt=8,rms=0.577294) #GCAMreg# pass 0 level1 3 level2 1 tsec 178.169 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.12 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=16, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.577568 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.573996) vs oldopt=(dt=32,rms=0.574302) #GCMRL# 391 dt 44.800000 rms 0.574 0.618% neg 0 invalid 762 tFOTS 6.6580 tGradient 1.9780 tsec 9.0960 #FOTS# QuadFit found better minimum quadopt=(dt=38.4,rms=0.573205) vs oldopt=(dt=32,rms=0.573205) #GCMRL# 392 dt 38.400000 rms 0.573 0.138% neg 0 invalid 762 tFOTS 6.5430 tGradient 1.8610 tsec 8.8960 #FOTS# QuadFit found better minimum quadopt=(dt=38.4,rms=0.57261) vs oldopt=(dt=32,rms=0.572615) #GCMRL# 393 dt 38.400000 rms 0.573 0.104% neg 0 invalid 762 tFOTS 6.6140 tGradient 1.8130 tsec 8.8930 #FOTS# QuadFit found better minimum quadopt=(dt=25.6,rms=0.572177) vs oldopt=(dt=32,rms=0.572179) #GCMRL# 394 dt 25.600000 rms 0.572 0.076% neg 0 invalid 762 tFOTS 6.5090 tGradient 1.9650 tsec 8.9620 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.571809) vs oldopt=(dt=32,rms=0.571862) #GCMRL# 395 dt 44.800000 rms 0.572 0.064% neg 0 invalid 762 tFOTS 6.1670 tGradient 1.9180 tsec 8.5660 #FOTS# QuadFit found better minimum quadopt=(dt=38.4,rms=0.571477) vs oldopt=(dt=32,rms=0.571482) #GCMRL# 396 dt 38.400000 rms 0.571 0.058% neg 0 invalid 762 tFOTS 6.0790 tGradient 1.9410 tsec 8.4980 #GCMRL# 397 dt 32.000000 rms 0.571 0.064% neg 0 invalid 762 tFOTS 6.9140 tGradient 1.9490 tsec 9.3620 #GCMRL# 398 dt 32.000000 rms 0.571 0.000% neg 0 invalid 762 tFOTS 6.9780 tGradient 2.0020 tsec 9.4870 #GCMRL# 399 dt 32.000000 rms 0.571 0.044% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9580 tsec 2.4530 #GCMRL# 400 dt 32.000000 rms 0.570 0.060% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.7850 tsec 2.2780 #GCMRL# 401 dt 32.000000 rms 0.570 0.065% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9680 tsec 2.4550 #GCMRL# 402 dt 32.000000 rms 0.570 0.053% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8970 tsec 2.3950 #GCMRL# 403 dt 32.000000 rms 0.569 0.062% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9060 tsec 2.4050 #GCMRL# 404 dt 32.000000 rms 0.569 0.066% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0140 tsec 2.5120 #GCMRL# 405 dt 32.000000 rms 0.569 0.040% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8690 tsec 2.3670 #GCMRL# 406 dt 32.000000 rms 0.568 0.063% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9250 tsec 2.3810 #GCMRL# 407 dt 32.000000 rms 0.568 0.070% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8590 tsec 2.3590 #GCMRL# 408 dt 32.000000 rms 0.568 0.066% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8790 tsec 2.3760 #GCMRL# 409 dt 32.000000 rms 0.567 0.060% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.7960 tsec 2.3040 #GCMRL# 410 dt 32.000000 rms 0.567 0.076% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.7400 tsec 2.2390 #GCMRL# 411 dt 32.000000 rms 0.566 0.080% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8520 tsec 2.3520 #GCMRL# 412 dt 32.000000 rms 0.566 0.072% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9940 tsec 2.4860 #GCMRL# 413 dt 32.000000 rms 0.566 0.050% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8510 tsec 2.3440 #GCMRL# 414 dt 32.000000 rms 0.565 0.066% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8150 tsec 2.3080 #GCMRL# 415 dt 32.000000 rms 0.565 0.058% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8890 tsec 2.3920 #GCMRL# 416 dt 32.000000 rms 0.564 0.067% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8130 tsec 2.3090 #GCMRL# 417 dt 32.000000 rms 0.564 0.051% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8450 tsec 2.3420 #GCMRL# 418 dt 32.000000 rms 0.564 0.050% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.7970 tsec 2.2230 #GCMRL# 419 dt 32.000000 rms 0.563 0.088% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8800 tsec 2.2850 #GCMRL# 420 dt 32.000000 rms 0.563 0.062% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8850 tsec 2.3820 #GCMRL# 421 dt 32.000000 rms 0.563 0.059% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9700 tsec 2.4700 #GCMRL# 422 dt 32.000000 rms 0.562 0.049% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8320 tsec 2.3280 #GCMRL# 423 dt 32.000000 rms 0.562 0.077% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9460 tsec 2.4210 #GCMRL# 424 dt 32.000000 rms 0.562 0.044% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.7580 tsec 2.2480 #GCMRL# 425 dt 32.000000 rms 0.562 0.042% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8210 tsec 2.3080 #GCMRL# 426 dt 32.000000 rms 0.561 0.046% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8360 tsec 2.3370 #GCMRL# 427 dt 32.000000 rms 0.561 0.064% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8760 tsec 2.3800 #GCMRL# 428 dt 32.000000 rms 0.561 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.7960 tsec 2.2920 #GCMRL# 429 dt 32.000000 rms 0.561 0.011% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8830 tsec 2.3370 #GCMRL# 430 dt 32.000000 rms 0.560 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9540 tsec 2.4430 #GCMRL# 431 dt 32.000000 rms 0.560 0.062% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8990 tsec 2.4010 #GCMRL# 432 dt 32.000000 rms 0.560 0.044% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8120 tsec 2.3090 #GCMRL# 433 dt 32.000000 rms 0.560 0.032% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8850 tsec 2.3840 #GCMRL# 434 dt 32.000000 rms 0.560 0.024% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8220 tsec 2.3100 #GCMRL# 435 dt 32.000000 rms 0.559 0.059% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9530 tsec 2.3740 #GCMRL# 436 dt 32.000000 rms 0.559 0.038% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9390 tsec 2.4320 #GCMRL# 437 dt 32.000000 rms 0.559 0.020% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8470 tsec 2.3500 #GCMRL# 438 dt 32.000000 rms 0.559 0.029% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.7360 tsec 2.2400 #GCMRL# 439 dt 32.000000 rms 0.559 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.7360 tsec 2.2310 #GCMRL# 440 dt 32.000000 rms 0.558 0.030% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.7720 tsec 2.2720 #GCMRL# 441 dt 32.000000 rms 0.558 0.031% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0010 tsec 2.5060 #GCMRL# 442 dt 32.000000 rms 0.558 0.024% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9180 tsec 2.4110 #GCMRL# 443 dt 32.000000 rms 0.558 0.042% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9160 tsec 2.4220 #GCMRL# 444 dt 32.000000 rms 0.558 0.025% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.7310 tsec 2.2370 #GCMRL# 445 dt 32.000000 rms 0.558 0.002% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8740 tsec 2.3710 #GCMRL# 446 dt 32.000000 rms 0.558 0.019% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9480 tsec 2.3600 #GCMRL# 447 dt 32.000000 rms 0.557 0.030% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9490 tsec 2.4260 #GCMRL# 448 dt 32.000000 rms 0.557 0.015% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8280 tsec 2.3370 #GCMRL# 449 dt 32.000000 rms 0.557 0.020% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8840 tsec 2.3810 #GCMRL# 450 dt 32.000000 rms 0.557 0.029% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9400 tsec 2.4330 #GCMRL# 451 dt 32.000000 rms 0.557 0.020% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8470 tsec 2.3390 #GCMRL# 452 dt 32.000000 rms 0.557 -0.002% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8780 tsec 2.8040 #FOTS# QuadFit found better minimum quadopt=(dt=6.4,rms=0.556924) vs oldopt=(dt=8,rms=0.556924) #GCMRL# 453 dt 6.400000 rms 0.557 0.001% neg 0 invalid 762 tFOTS 6.4960 tGradient 1.9450 tsec 8.9370 #FOTS# QuadFit found better minimum quadopt=(dt=0.7,rms=0.556919) vs oldopt=(dt=0.5,rms=0.556919) setting smoothness cost coefficient to 0.400 #GCAMreg# pass 0 level1 2 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.40 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=4, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.579955 #GCMRL# 455 dt 0.000000 rms 0.580 0.046% neg 0 invalid 762 tFOTS 6.0760 tGradient 1.8130 tsec 8.3710 #GCAMreg# pass 0 level1 2 level2 1 tsec 20.047 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.40 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=4, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.579955 #GCMRL# 457 dt 0.000000 rms 0.580 0.046% neg 0 invalid 762 tFOTS 6.0620 tGradient 1.8620 tsec 8.4090 setting smoothness cost coefficient to 1.000 #GCAMreg# pass 0 level1 1 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=1.00 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=1, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.62558 #FOTS# QuadFit found better minimum quadopt=(dt=0.768,rms=0.623739) vs oldopt=(dt=1.28,rms=0.624183) #GCMRL# 459 dt 0.768000 rms 0.624 0.294% neg 0 invalid 762 tFOTS 5.9630 tGradient 1.7650 tsec 8.2060 #FOTS# QuadFit found better minimum quadopt=(dt=0.112,rms=0.623698) vs oldopt=(dt=0.08,rms=0.623704) #GCMRL# 460 dt 0.112000 rms 0.624 0.000% neg 0 invalid 762 tFOTS 6.1960 tGradient 1.7400 tsec 8.3990 #GCMRL# 461 dt 0.112000 rms 0.624 0.000% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8090 tsec 2.3150 #GCAMreg# pass 0 level1 1 level2 1 tsec 24.482 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=1.00 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=1, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.623949 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.623183) vs oldopt=(dt=0.32,rms=0.623273) #GCMRL# 463 dt 0.448000 rms 0.623 0.123% neg 0 invalid 762 tFOTS 6.0140 tGradient 1.8410 tsec 8.3110 #GCMRL# 464 dt 0.320000 rms 0.623 0.000% neg 0 invalid 762 tFOTS 6.0500 tGradient 1.7670 tsec 8.3320 resetting metric properties... setting smoothness cost coefficient to 2.000 #GCAMreg# pass 0 level1 0 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=2.00 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=0, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.563782 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.548231) vs oldopt=(dt=0.32,rms=0.552434) #GCMRL# 466 dt 0.448000 rms 0.548 2.758% neg 0 invalid 762 tFOTS 5.6550 tGradient 1.3110 tsec 7.4480 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.545156) vs oldopt=(dt=0.32,rms=0.546043) #GCMRL# 467 dt 0.448000 rms 0.545 0.561% neg 0 invalid 762 tFOTS 5.6310 tGradient 1.3120 tsec 7.4260 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.543555) vs oldopt=(dt=0.32,rms=0.544) #GCMRL# 468 dt 0.448000 rms 0.544 0.294% neg 0 invalid 762 tFOTS 5.6940 tGradient 1.3880 tsec 7.5740 #FOTS# QuadFit found better minimum quadopt=(dt=0.472222,rms=0.542631) vs oldopt=(dt=0.32,rms=0.542919) #GCMRL# 469 dt 0.472222 rms 0.543 0.170% neg 0 invalid 762 tFOTS 5.6660 tGradient 1.3400 tsec 7.4710 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.541973) vs oldopt=(dt=0.32,rms=0.542156) #GCMRL# 470 dt 0.448000 rms 0.542 0.121% neg 0 invalid 762 tFOTS 5.7050 tGradient 1.3520 tsec 7.5620 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.54149) vs oldopt=(dt=0.32,rms=0.541615) #GCMRL# 471 dt 0.448000 rms 0.541 0.089% neg 0 invalid 762 tFOTS 5.7820 tGradient 1.2450 tsec 7.5320 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.54111) vs oldopt=(dt=0.32,rms=0.541211) #GCMRL# 472 dt 0.448000 rms 0.541 0.070% neg 0 invalid 762 tFOTS 5.6530 tGradient 1.1510 tsec 7.2910 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.540827) vs oldopt=(dt=0.32,rms=0.540896) #GCMRL# 473 dt 0.448000 rms 0.541 0.052% neg 0 invalid 762 tFOTS 5.6420 tGradient 1.2370 tsec 7.3670 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.540574) vs oldopt=(dt=0.32,rms=0.540636) #GCMRL# 474 dt 0.448000 rms 0.541 0.000% neg 0 invalid 762 tFOTS 5.5980 tGradient 1.2500 tsec 7.3490 #GCMRL# 475 dt 0.448000 rms 0.540 0.032% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.2420 tsec 1.7330 #GCMRL# 476 dt 0.448000 rms 0.540 0.063% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.3550 tsec 1.8610 #GCMRL# 477 dt 0.448000 rms 0.540 0.073% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.3880 tsec 1.8780 #GCMRL# 478 dt 0.448000 rms 0.539 0.068% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.2520 tsec 1.7370 #GCMRL# 479 dt 0.448000 rms 0.539 0.046% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.2560 tsec 1.7440 #GCMRL# 480 dt 0.448000 rms 0.539 0.027% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.3000 tsec 1.8040 #GCMRL# 481 dt 0.448000 rms 0.539 0.008% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.2620 tsec 1.7470 #GCMRL# 482 dt 0.448000 rms 0.539 -0.009% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.3550 tsec 2.2790 #GCMRL# 483 dt 0.080000 rms 0.539 0.001% neg 0 invalid 762 tFOTS 5.6350 tGradient 1.1780 tsec 7.3220 #FOTS# QuadFit found better minimum quadopt=(dt=0.028,rms=0.53886) vs oldopt=(dt=0.02,rms=0.53886) #GCAMreg# pass 0 level1 0 level2 1 tsec 99.711 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=2.00 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=0, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.539161 #FOTS# QuadFit found better minimum quadopt=(dt=0.384,rms=0.531874) vs oldopt=(dt=0.32,rms=0.532976) #GCMRL# 485 dt 0.384000 rms 0.532 1.351% neg 0 invalid 762 tFOTS 5.5930 tGradient 1.2150 tsec 7.2830 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.529129) vs oldopt=(dt=0.32,rms=0.529882) #GCMRL# 486 dt 0.448000 rms 0.529 0.516% neg 0 invalid 762 tFOTS 5.6830 tGradient 1.2150 tsec 7.3950 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.528406) vs oldopt=(dt=0.32,rms=0.528595) #GCMRL# 487 dt 0.448000 rms 0.528 0.137% neg 0 invalid 762 tFOTS 5.7570 tGradient 1.2440 tsec 7.4890 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.528124) vs oldopt=(dt=0.32,rms=0.52819) #GCMRL# 488 dt 0.448000 rms 0.528 0.053% neg 0 invalid 762 tFOTS 5.5700 tGradient 1.2690 tsec 7.3120 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.528) vs oldopt=(dt=0.32,rms=0.528021) #GCMRL# 489 dt 0.448000 rms 0.528 0.000% neg 0 invalid 762 tFOTS 5.7450 tGradient 1.2690 tsec 7.5280 #GCMRL# 490 dt 0.448000 rms 0.528 0.021% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.2910 tsec 1.8130 #GCMRL# 491 dt 0.448000 rms 0.528 0.011% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.3130 tsec 2.0580 #GCMRL# 492 dt 0.448000 rms 0.528 0.020% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.2660 tsec 1.7490 #GCMRL# 493 dt 0.448000 rms 0.528 0.004% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.3210 tsec 2.0620 #FOTS# QuadFit found better minimum quadopt=(dt=0.256,rms=0.527698) vs oldopt=(dt=0.32,rms=0.5277) GCAMregister done in 28.0358 min ********************* ALLOWING NEGATIVE NODES IN DEFORMATION******************************** noneg post Starting GCAMregister() label assignment complete, 0 changed (0.00%) npasses = 1, nlevels = 6 #pass# 1 of 1 ************************ enabling zero nodes setting smoothness cost coefficient to 0.008 #GCAMreg# pass 0 level1 5 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.01 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=256, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.525607 #GCMRL# 495 dt 0.000000 rms 0.525 0.061% neg 0 invalid 762 tFOTS 6.9570 tGradient 2.3580 tsec 9.8040 #GCAMreg# pass 0 level1 5 level2 1 tsec 22.742 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.01 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=256, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.525607 #FOTS# QuadFit found better minimum quadopt=(dt=0.0180625,rms=0.525287) vs oldopt=(dt=0.0225781,rms=0.525287) #GCMRL# 497 dt 0.018063 rms 0.525 0.061% neg 0 invalid 762 tFOTS 7.2580 tGradient 2.5750 tsec 10.3190 setting smoothness cost coefficient to 0.031 #GCAMreg# pass 0 level1 4 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.03 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=64, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.525635 #GCMRL# 499 dt 0.000000 rms 0.525 0.061% neg 0 invalid 762 tFOTS 6.9630 tGradient 2.1490 tsec 9.5980 #GCAMreg# pass 0 level1 4 level2 1 tsec 22.352 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.03 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=64, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.525635 #FOTS# QuadFit found better minimum quadopt=(dt=80.7943,rms=0.5243) vs oldopt=(dt=103.68,rms=0.524387) #GCMRL# 501 dt 80.794326 rms 0.524 0.254% neg 0 invalid 762 tFOTS 7.2850 tGradient 2.0930 tsec 9.8670 #FOTS# QuadFit found better minimum quadopt=(dt=76.6131,rms=0.523395) vs oldopt=(dt=103.68,rms=0.523484) #GCMRL# 502 dt 76.613139 rms 0.523 0.000% neg 0 invalid 762 tFOTS 7.3640 tGradient 1.9870 tsec 9.8710 setting smoothness cost coefficient to 0.118 #GCAMreg# pass 0 level1 3 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.12 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=16, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.523835 #FOTS# QuadFit found better minimum quadopt=(dt=9.6,rms=0.522816) vs oldopt=(dt=8,rms=0.522848) #GCMRL# 504 dt 9.600000 rms 0.523 0.194% neg 0 invalid 762 tFOTS 7.2650 tGradient 1.8440 tsec 9.5880 #FOTS# QuadFit found better minimum quadopt=(dt=4.8,rms=0.522708) vs oldopt=(dt=8,rms=0.522729) #GCMRL# 505 dt 4.800000 rms 0.523 0.000% neg 0 invalid 762 tFOTS 7.1750 tGradient 1.9020 tsec 9.5630 #GCMRL# 506 dt 4.800000 rms 0.523 0.002% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.7330 tsec 2.1380 #GCAMreg# pass 0 level1 3 level2 1 tsec 26.809 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.12 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=16, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.522998 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.517171) vs oldopt=(dt=32,rms=0.517645) #GCMRL# 508 dt 44.800000 rms 0.517 1.114% neg 0 invalid 762 tFOTS 7.2730 tGradient 2.0220 tsec 9.7810 #FOTS# QuadFit found better minimum quadopt=(dt=24.7887,rms=0.515291) vs oldopt=(dt=32,rms=0.515508) #GCMRL# 509 dt 24.788732 rms 0.515 0.363% neg 0 invalid 762 tFOTS 7.2310 tGradient 1.9810 tsec 9.6960 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.514085) vs oldopt=(dt=32,rms=0.514147) #GCMRL# 510 dt 44.800000 rms 0.514 0.000% neg 0 invalid 762 tFOTS 7.3150 tGradient 1.7790 tsec 9.5790 iter 0, gcam->neg = 1 after 1 iterations, nbhd size=0, neg = 0 #GCMRL# 511 dt 44.800000 rms 0.514 0.011% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9290 tsec 3.5600 #GCMRL# 512 dt 44.800000 rms 0.511 0.515% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.7970 tsec 2.2930 #GCMRL# 513 dt 44.800000 rms 0.509 0.440% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9790 tsec 2.4740 #GCMRL# 514 dt 44.800000 rms 0.507 0.347% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.8720 tsec 2.3730 #GCMRL# 515 dt 44.800000 rms 0.506 0.254% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0150 tsec 2.5050 #GCMRL# 516 dt 44.800000 rms 0.505 0.269% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0300 tsec 2.5150 #GCMRL# 517 dt 44.800000 rms 0.504 0.226% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.7870 tsec 2.2800 #GCMRL# 518 dt 44.800000 rms 0.502 0.215% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9030 tsec 2.3980 #GCMRL# 519 dt 44.800000 rms 0.502 0.042% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9930 tsec 2.4780 #GCMRL# 520 dt 44.800000 rms 0.502 0.100% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9890 tsec 2.4600 #GCMRL# 521 dt 44.800000 rms 0.501 0.134% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9920 tsec 2.4750 #GCMRL# 522 dt 44.800000 rms 0.501 0.066% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.0950 tsec 2.5940 #GCMRL# 523 dt 44.800000 rms 0.501 0.052% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9560 tsec 2.4660 #FOTS# QuadFit found better minimum quadopt=(dt=11.2,rms=0.499926) vs oldopt=(dt=8,rms=0.500037) #GCMRL# 524 dt 11.200000 rms 0.500 0.116% neg 0 invalid 762 tFOTS 7.1730 tGradient 1.9990 tsec 9.6660 #FOTS# QuadFit found better minimum quadopt=(dt=25.6,rms=0.499652) vs oldopt=(dt=32,rms=0.499661) #GCMRL# 525 dt 25.600000 rms 0.500 0.000% neg 0 invalid 762 tFOTS 7.2200 tGradient 2.1630 tsec 9.8750 #GCMRL# 526 dt 25.600000 rms 0.500 0.007% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1240 tsec 2.6210 #GCMRL# 527 dt 25.600000 rms 0.500 0.020% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.2770 tsec 2.7590 #GCMRL# 528 dt 25.600000 rms 0.499 0.021% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1690 tsec 2.6670 #GCMRL# 529 dt 25.600000 rms 0.499 0.008% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.1390 tsec 2.6520 setting smoothness cost coefficient to 0.400 #GCAMreg# pass 0 level1 2 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.40 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=4, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.503661 #GCMRL# 531 dt 0.000000 rms 0.503 0.068% neg 0 invalid 762 tFOTS 6.9810 tGradient 1.9830 tsec 9.4620 #GCAMreg# pass 0 level1 2 level2 1 tsec 22.138 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.40 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=4, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.503661 #FOTS# QuadFit found better minimum quadopt=(dt=2.2,rms=0.503235) vs oldopt=(dt=2.88,rms=0.503242) #GCMRL# 533 dt 2.200000 rms 0.503 0.085% neg 0 invalid 762 tFOTS 7.4150 tGradient 2.0670 tsec 9.9850 #FOTS# QuadFit found better minimum quadopt=(dt=1.008,rms=0.503209) vs oldopt=(dt=0.72,rms=0.503213) #GCMRL# 534 dt 1.008000 rms 0.503 0.000% neg 0 invalid 762 tFOTS 7.3800 tGradient 1.8790 tsec 9.7680 #GCMRL# 535 dt 1.008000 rms 0.503 0.002% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9980 tsec 2.4870 setting smoothness cost coefficient to 1.000 #GCAMreg# pass 0 level1 1 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=1.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=1, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.510648 #FOTS# QuadFit found better minimum quadopt=(dt=0.256,rms=0.510283) vs oldopt=(dt=0.32,rms=0.510285) #GCMRL# 537 dt 0.256000 rms 0.510 0.072% neg 0 invalid 762 tFOTS 7.1560 tGradient 1.7160 tsec 9.3620 #FOTS# QuadFit found better minimum quadopt=(dt=0.028,rms=0.510289) vs oldopt=(dt=0.02,rms=0.510289) #GCAMreg# pass 0 level1 1 level2 1 tsec 22.347 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=1.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=1, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.510598 #FOTS# QuadFit found better minimum quadopt=(dt=1.792,rms=0.508563) vs oldopt=(dt=1.28,rms=0.508693) #GCMRL# 539 dt 1.792000 rms 0.509 0.398% neg 0 invalid 762 tFOTS 7.1150 tGradient 1.9770 tsec 9.5620 #FOTS# QuadFit found better minimum quadopt=(dt=1.792,rms=0.508084) vs oldopt=(dt=1.28,rms=0.508117) #GCMRL# 540 dt 1.792000 rms 0.508 0.000% neg 0 invalid 762 tFOTS 7.3670 tGradient 2.0720 tsec 9.9390 #GCMRL# 541 dt 1.792000 rms 0.508 0.027% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.7700 tsec 2.2810 resetting metric properties... setting smoothness cost coefficient to 2.000 #GCAMreg# pass 0 level1 0 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=2.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=0, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.503145 #FOTS# QuadFit found better minimum quadopt=(dt=1.91735,rms=0.471358) vs oldopt=(dt=1.28,rms=0.475104) iter 0, gcam->neg = 356 after 15 iterations, nbhd size=1, neg = 0 #GCMRL# 543 dt 1.917348 rms 0.473 5.929% neg 0 invalid 762 tFOTS 7.2490 tGradient 1.3110 tsec 15.1710 #FOTS# QuadFit found better minimum quadopt=(dt=0.048,rms=0.473206) vs oldopt=(dt=0.08,rms=0.473235) #GCMRL# 544 dt 0.048000 rms 0.473 0.000% neg 0 invalid 762 tFOTS 7.1430 tGradient 1.3470 tsec 8.9940 #GCAMreg# pass 0 level1 0 level2 1 tsec 29.373 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=2.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=0, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.473606 #FOTS# QuadFit found better minimum quadopt=(dt=0.112,rms=0.472484) vs oldopt=(dt=0.08,rms=0.472599) #GCMRL# 546 dt 0.112000 rms 0.472 0.237% neg 0 invalid 762 tFOTS 7.0210 tGradient 1.4080 tsec 8.9050 #FOTS# QuadFit found better minimum quadopt=(dt=0.028,rms=0.472439) vs oldopt=(dt=0.02,rms=0.472449) #GCMRL# 547 dt 0.028000 rms 0.472 0.000% neg 0 invalid 762 tFOTS 7.2410 tGradient 1.2990 tsec 9.0450 #GCMRL# 548 dt 0.028000 rms 0.472 0.002% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.2360 tsec 1.7250 label assignment complete, 0 changed (0.00%) GCAMregister done in 6.09767 min Starting GCAMcomputeMaxPriorLabels() Morphing with label term set to 0 ******************************* Starting GCAMregister() label assignment complete, 0 changed (0.00%) npasses = 1, nlevels = 6 #pass# 1 of 1 ************************ enabling zero nodes setting smoothness cost coefficient to 0.008 #GCAMreg# pass 0 level1 5 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=0.01 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=256, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.461425 #GCAMreg# pass 0 level1 5 level2 1 tsec 12.311 sigma 0.5 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=0.01 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=256, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.461425 setting smoothness cost coefficient to 0.031 #GCAMreg# pass 0 level1 4 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=0.03 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=64, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.461558 #GCAMreg# pass 0 level1 4 level2 1 tsec 11.67 sigma 0.5 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=0.03 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=64, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.461558 #FOTS# QuadFit found better minimum quadopt=(dt=15.552,rms=0.461513) vs oldopt=(dt=25.92,rms=0.461524) #GCMRL# 553 dt 15.552000 rms 0.462 0.010% neg 0 invalid 762 tFOTS 6.3660 tGradient 1.4910 tsec 8.2380 #FOTS# QuadFit found better minimum quadopt=(dt=9.072,rms=0.461504) vs oldopt=(dt=6.48,rms=0.461505) #GCMRL# 554 dt 9.072000 rms 0.462 0.000% neg 0 invalid 762 tFOTS 6.8440 tGradient 1.4710 tsec 8.7950 #GCMRL# 555 dt 9.072000 rms 0.462 0.001% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.4880 tsec 1.9790 setting smoothness cost coefficient to 0.118 #GCAMreg# pass 0 level1 3 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=0.12 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=16, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.462004 #GCMRL# 557 dt 0.001953 rms 0.462 0.000% neg 0 invalid 762 tFOTS 6.8890 tGradient 1.3220 tsec 8.6840 #GCAMreg# pass 0 level1 3 level2 1 tsec 20.112 sigma 0.5 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=0.12 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=16, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.462004 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.460439) vs oldopt=(dt=32,rms=0.460557) #GCMRL# 559 dt 44.800000 rms 0.460 0.339% neg 0 invalid 762 tFOTS 6.8550 tGradient 1.3380 tsec 8.6630 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.459404) vs oldopt=(dt=32,rms=0.459513) #GCMRL# 560 dt 44.800000 rms 0.459 0.000% neg 0 invalid 762 tFOTS 6.8020 tGradient 1.1840 tsec 8.4280 #GCMRL# 561 dt 44.800000 rms 0.459 0.023% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.3240 tsec 1.7930 #GCMRL# 562 dt 44.800000 rms 0.458 0.233% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.3190 tsec 1.8000 #GCMRL# 563 dt 44.800000 rms 0.458 0.146% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.2340 tsec 1.7100 iter 0, gcam->neg = 2 after 1 iterations, nbhd size=0, neg = 0 #GCMRL# 564 dt 44.800000 rms 0.457 0.158% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.3180 tsec 2.6900 #GCMRL# 565 dt 44.800000 rms 0.456 0.104% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.3130 tsec 1.7920 iter 0, gcam->neg = 1 after 1 iterations, nbhd size=0, neg = 0 #GCMRL# 566 dt 44.800000 rms 0.456 0.103% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.2020 tsec 2.6250 #FOTS# QuadFit found better minimum quadopt=(dt=11.2,rms=0.455556) vs oldopt=(dt=8,rms=0.455624) #GCMRL# 567 dt 11.200000 rms 0.456 0.000% neg 0 invalid 762 tFOTS 6.8890 tGradient 1.3260 tsec 8.7160 #GCMRL# 568 dt 11.200000 rms 0.455 0.021% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.3350 tsec 1.8180 #GCMRL# 569 dt 11.200000 rms 0.455 0.024% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.3380 tsec 1.8150 #GCMRL# 570 dt 11.200000 rms 0.455 0.024% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.3170 tsec 1.8150 #GCMRL# 571 dt 11.200000 rms 0.455 0.025% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.3240 tsec 1.8040 setting smoothness cost coefficient to 0.400 #GCAMreg# pass 0 level1 2 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=0.40 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=4, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.457987 #GCAMreg# pass 0 level1 2 level2 1 tsec 11.491 sigma 0.5 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=0.40 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=4, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.457987 #FOTS# QuadFit found better minimum quadopt=(dt=12.2353,rms=0.45692) vs oldopt=(dt=11.52,rms=0.456924) #GCMRL# 574 dt 12.235294 rms 0.457 0.233% neg 0 invalid 762 tFOTS 6.9160 tGradient 1.2170 tsec 8.5910 #FOTS# QuadFit found better minimum quadopt=(dt=30.0812,rms=0.455365) vs oldopt=(dt=46.08,rms=0.455861) iter 0, gcam->neg = 2 after 1 iterations, nbhd size=0, neg = 0 #GCMRL# 575 dt 30.081238 rms 0.455 0.336% neg 0 invalid 762 tFOTS 6.8730 tGradient 1.2360 tsec 9.5290 #FOTS# QuadFit found better minimum quadopt=(dt=8.5,rms=0.454794) vs oldopt=(dt=11.52,rms=0.45487) #GCMRL# 576 dt 8.500000 rms 0.455 0.000% neg 0 invalid 762 tFOTS 6.8550 tGradient 1.2260 tsec 8.5660 #GCMRL# 577 dt 8.500000 rms 0.454 0.080% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.2440 tsec 1.7240 #GCMRL# 578 dt 8.500000 rms 0.454 0.115% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.1040 tsec 1.5880 iter 0, gcam->neg = 3 after 0 iterations, nbhd size=0, neg = 0 #GCMRL# 579 dt 8.500000 rms 0.453 0.155% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.2320 tsec 2.3730 #GCMRL# 580 dt 8.500000 rms 0.453 0.136% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.1140 tsec 1.5970 #GCMRL# 581 dt 8.500000 rms 0.452 0.125% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.2100 tsec 1.7030 iter 0, gcam->neg = 2 after 1 iterations, nbhd size=0, neg = 0 #GCMRL# 582 dt 8.500000 rms 0.452 0.099% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.2380 tsec 2.7040 #FOTS# QuadFit found better minimum quadopt=(dt=9.216,rms=0.451482) vs oldopt=(dt=11.52,rms=0.451484) iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 #GCMRL# 583 dt 9.216000 rms 0.451 0.000% neg 0 invalid 762 tFOTS 6.8870 tGradient 1.2200 tsec 9.2380 setting smoothness cost coefficient to 1.000 #GCAMreg# pass 0 level1 1 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=1.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=1, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.456412 #GCAMreg# pass 0 level1 1 level2 1 tsec 11.299 sigma 0.5 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=1.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=1, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.456412 #FOTS# QuadFit found better minimum quadopt=(dt=6e-05,rms=0.456411) vs oldopt=(dt=5e-05,rms=0.456411) #GCMRL# 586 dt 0.000060 rms 0.456 0.000% neg 0 invalid 762 tFOTS 8.5630 tGradient 1.1700 tsec 10.2100 resetting metric properties... setting smoothness cost coefficient to 2.000 #GCAMreg# pass 0 level1 0 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=2.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=0, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.448164 iter 0, gcam->neg = 269 after 15 iterations, nbhd size=1, neg = 0 #GCMRL# 588 dt 1.280000 rms 0.441 1.608% neg 0 invalid 762 tFOTS 6.8460 tGradient 0.7230 tsec 14.1650 #FOTS# QuadFit found better minimum quadopt=(dt=2.34375e-05,rms=0.440956) vs oldopt=(dt=1.95313e-05,rms=0.440956) #GCMRL# 589 dt 0.000023 rms 0.441 0.000% neg 0 invalid 762 tFOTS 8.7030 tGradient 0.7540 tsec 9.9120 #GCAMreg# pass 0 level1 0 level2 1 tsec 28.618 sigma 0.5 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=2.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=0, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.440956 #FOTS# QuadFit found better minimum quadopt=(dt=0.256,rms=0.439539) vs oldopt=(dt=0.32,rms=0.439609) #GCMRL# 591 dt 0.256000 rms 0.440 0.321% neg 0 invalid 762 tFOTS 6.9010 tGradient 0.7160 tsec 8.0810 #FOTS# QuadFit found better minimum quadopt=(dt=0.384,rms=0.438369) vs oldopt=(dt=0.32,rms=0.438418) #GCMRL# 592 dt 0.384000 rms 0.438 0.266% neg 0 invalid 762 tFOTS 7.0600 tGradient 0.6880 tsec 8.2270 #FOTS# QuadFit found better minimum quadopt=(dt=0.865052,rms=0.435686) vs oldopt=(dt=1.28,rms=0.436322) iter 0, gcam->neg = 145 after 12 iterations, nbhd size=1, neg = 0 #GCMRL# 593 dt 0.865052 rms 0.437 0.354% neg 0 invalid 762 tFOTS 6.9800 tGradient 0.6220 tsec 12.9770 #GCMRL# 594 dt 0.320000 rms 0.436 0.000% neg 0 invalid 762 tFOTS 6.9360 tGradient 0.7650 tsec 8.1930 #GCMRL# 595 dt 0.320000 rms 0.436 0.121% neg 0 invalid 762 tFOTS 0.0000 tGradient 0.7350 tsec 1.2120 iter 0, gcam->neg = 5 after 0 iterations, nbhd size=0, neg = 0 #GCMRL# 596 dt 0.320000 rms 0.435 0.145% neg 0 invalid 762 tFOTS 0.0000 tGradient 0.7250 tsec 1.9250 iter 0, gcam->neg = 9 after 4 iterations, nbhd size=0, neg = 0 #GCMRL# 597 dt 0.320000 rms 0.435 0.129% neg 0 invalid 762 tFOTS 0.0000 tGradient 0.7670 tsec 3.4250 iter 0, gcam->neg = 14 after 3 iterations, nbhd size=0, neg = 0 #GCMRL# 598 dt 0.320000 rms 0.434 0.074% neg 0 invalid 762 tFOTS 0.0000 tGradient 0.7080 tsec 2.9580 iter 0, gcam->neg = 32 after 12 iterations, nbhd size=1, neg = 0 #GCMRL# 599 dt 0.320000 rms 0.434 -0.091% neg 0 invalid 762 tFOTS 0.0000 tGradient 0.7610 tsec 6.6240 #FOTS# QuadFit found better minimum quadopt=(dt=0.112,rms=0.434238) vs oldopt=(dt=0.08,rms=0.434246) #GCMRL# 600 dt 0.112000 rms 0.434 0.011% neg 0 invalid 762 tFOTS 7.0720 tGradient 0.7340 tsec 8.2900 #FOTS# QuadFit found better minimum quadopt=(dt=0.256,rms=0.434189) vs oldopt=(dt=0.32,rms=0.43419) iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 #GCMRL# 601 dt 0.256000 rms 0.434 0.011% neg 0 invalid 762 tFOTS 7.0300 tGradient 0.7490 tsec 8.9890 #FOTS# QuadFit found better minimum quadopt=(dt=0.192,rms=0.434169) vs oldopt=(dt=0.32,rms=0.434175) GCAMregister done in 5.52678 min writing output transformation to transforms/talairach.m3z... GCAMwrite Calls to gcamLogLikelihoodEnergy 4030 tmin = 5.47098 Calls to gcamLabelEnergy 3415 tmin = 0.853417 Calls to gcamJacobianEnergy 4030 tmin = 4.12385 Calls to gcamSmoothnessEnergy 4030 tmin = 4.86853 Calls to gcamLogLikelihoodTerm 603 tmin = 1.3823 Calls to gcamLabelTerm 550 tmin = 6.8639 Calls to gcamJacobianTerm 603 tmin = 2.98478 Calls to gcamSmoothnessTerm 603 tmin = 1.38178 Calls to gcamComputeGradient 603 tmin = 21.2686 Calls to gcamComputeMetricProperties 5581 tmin = 6.5715 mri_ca_register took 0 hours, 53 minutes and 15 seconds. #VMPC# mri_ca_register VmPeak 2325672 FSRUNTIME@ mri_ca_register 0.8874 hours 4 threads @#@FSTIME 2021:11:09:17:42:44 mri_ca_register N 9 e 3194.63 S 1.14 U 9005.12 P 281% M 1320844 F 7 R 721115 W 0 c 19536 w 29653 I 2176 O 64960 L 1.79 2.42 1.55 @#@FSLOADPOST 2021:11:09:18:35:59 mri_ca_register N 9 3.35 3.14 2.96 #-------------------------------------- #@# SubCort Seg Tue Nov 9 18:35:59 EST 2021 mri_ca_label -relabel_unlikely 9 .3 -prior 0.5 -align norm.mgz transforms/talairach.m3z /home/basuia/Documents/mmvt_root/freesurfer/average/RB_all_2020-01-02.gca aseg.auto_noCCseg.mgz sysname Linux hostname Ishita-Ubuntu machine x86_64 setenv SUBJECTS_DIR /home/basuia/Documents/mmvt_root/subjects cd /home/basuia/Documents/mmvt_root/subjects/UC07/mri mri_ca_label -relabel_unlikely 9 .3 -prior 0.5 -align norm.mgz transforms/talairach.m3z /home/basuia/Documents/mmvt_root/freesurfer/average/RB_all_2020-01-02.gca aseg.auto_noCCseg.mgz relabeling unlikely voxels with window_size = 9 and prior threshold 0.30 using Gibbs prior factor = 0.500 renormalizing sequences with structure alignment, equivalent to: -renormalize -renormalize_mean 0.500 -regularize 0.500 == Number of threads available to for OpenMP = 4 == reading 1 input volumes reading classifier array from /home/basuia/Documents/mmvt_root/freesurfer/average/RB_all_2020-01-02.gca reading input volume from norm.mgz average std[0] = 7.2 reading transform from transforms/talairach.m3z setting orig areas to linear transform determinant scaled 8.42 Atlas used for the 3D morph was /home/basuia/Documents/mmvt_root/freesurfer/average/RB_all_2020-01-02.gca average std = 7.2 using min determinant for regularization = 5.2 0 singular and 0 ill-conditioned covariance matrices regularized labeling volume... renormalizing by structure alignment.... renormalizing input #0 gca peak = 0.15521 (20) mri peak = 0.08977 (39) Left_Lateral_Ventricle (4): linear fit = 1.88 x + 0.0 (2087 voxels, overlap=0.055) Left_Lateral_Ventricle (4): linear fit = 1.50 x + 0.0 (2087 voxels, peak = 38), gca=30.0 gca peak = 0.20380 (13) mri peak = 0.06346 (28) Right_Lateral_Ventricle (43): linear fit = 1.89 x + 0.0 (1277 voxels, overlap=0.322) Right_Lateral_Ventricle (43): linear fit = 1.50 x + 0.0 (1277 voxels, peak = 25), gca=19.5 gca peak = 0.26283 (96) mri peak = 0.07283 (99) Right_Pallidum (52): linear fit = 1.05 x + 0.0 (347 voxels, overlap=0.956) Right_Pallidum (52): linear fit = 1.05 x + 0.0 (347 voxels, peak = 101), gca=101.3 gca peak = 0.15814 (97) mri peak = 0.06654 (98) Left_Pallidum (13): linear fit = 1.03 x + 0.0 (139 voxels, overlap=0.848) Left_Pallidum (13): linear fit = 1.03 x + 0.0 (139 voxels, peak = 100), gca=100.4 gca peak = 0.27624 (56) mri peak = 0.07964 (67) Right_Hippocampus (53): linear fit = 1.21 x + 0.0 (429 voxels, overlap=0.022) Right_Hippocampus (53): linear fit = 1.21 x + 0.0 (429 voxels, peak = 67), gca=67.5 gca peak = 0.28723 (59) mri peak = 0.10243 (80) Left_Hippocampus (17): linear fit = 1.35 x + 0.0 (381 voxels, overlap=0.027) Left_Hippocampus (17): linear fit = 1.35 x + 0.0 (381 voxels, peak = 79), gca=79.4 gca peak = 0.07623 (103) mri peak = 0.05540 (101) Right_Cerebral_White_Matter (41): linear fit = 1.01 x + 0.0 (41334 voxels, overlap=0.901) Right_Cerebral_White_Matter (41): linear fit = 1.01 x + 0.0 (41334 voxels, peak = 105), gca=104.5 gca peak = 0.07837 (105) mri peak = 0.06051 (102) Left_Cerebral_White_Matter (2): linear fit = 1.00 x + 0.0 (43076 voxels, overlap=0.882) Left_Cerebral_White_Matter (2): linear fit = 1.00 x + 0.0 (43076 voxels, peak = 106), gca=105.5 gca peak = 0.10165 (58) mri peak = 0.04418 (88) Left_Cerebral_Cortex (3): linear fit = 1.47 x + 0.0 (25103 voxels, overlap=0.000) Left_Cerebral_Cortex (3): linear fit = 1.47 x + 0.0 (25103 voxels, peak = 85), gca=85.0 gca peak = 0.11113 (58) mri peak = 0.03911 (80) Right_Cerebral_Cortex (42): linear fit = 1.40 x + 0.0 (24552 voxels, overlap=0.000) Right_Cerebral_Cortex (42): linear fit = 1.40 x + 0.0 (24552 voxels, peak = 81), gca=81.5 gca peak = 0.27796 (67) mri peak = 0.09532 (91) Right_Caudate (50): linear fit = 1.29 x + 0.0 (601 voxels, overlap=0.026) Right_Caudate (50): linear fit = 1.29 x + 0.0 (601 voxels, peak = 87), gca=86.8 gca peak = 0.14473 (69) mri peak = 0.09326 (83) Left_Caudate (11): linear fit = 1.13 x + 0.0 (674 voxels, overlap=0.228) Left_Caudate (11): linear fit = 1.13 x + 0.0 (674 voxels, peak = 78), gca=78.3 gca peak = 0.14301 (56) mri peak = 0.05446 (72) Left_Cerebellum_Cortex (8): linear fit = 1.34 x + 0.0 (9415 voxels, overlap=0.002) Left_Cerebellum_Cortex (8): linear fit = 1.34 x + 0.0 (9415 voxels, peak = 75), gca=74.8 gca peak = 0.14610 (55) mri peak = 0.05719 (67) Right_Cerebellum_Cortex (47): linear fit = 1.25 x + 0.0 (10631 voxels, overlap=0.164) Right_Cerebellum_Cortex (47): linear fit = 1.25 x + 0.0 (10631 voxels, peak = 68), gca=68.5 gca peak = 0.16309 (85) mri peak = 0.06982 (87) Left_Cerebellum_White_Matter (7): linear fit = 1.07 x + 0.0 (4367 voxels, overlap=0.892) Left_Cerebellum_White_Matter (7): linear fit = 1.07 x + 0.0 (4367 voxels, peak = 91), gca=90.5 gca peak = 0.15172 (84) mri peak = 0.06288 (80) Right_Cerebellum_White_Matter (46): linear fit = 1.00 x + 0.0 (4129 voxels, overlap=0.996) Right_Cerebellum_White_Matter (46): linear fit = 1.00 x + 0.0 (4129 voxels, peak = 84), gca=83.6 gca peak = 0.30461 (58) mri peak = 0.08949 (74) Left_Amygdala (18): linear fit = 1.28 x + 0.0 (257 voxels, overlap=0.061) Left_Amygdala (18): linear fit = 1.28 x + 0.0 (257 voxels, peak = 75), gca=74.5 gca peak = 0.32293 (57) mri peak = 0.06418 (65) Right_Amygdala (54): linear fit = 1.24 x + 0.0 (385 voxels, overlap=0.311) Right_Amygdala (54): linear fit = 1.24 x + 0.0 (385 voxels, peak = 70), gca=70.4 gca peak = 0.11083 (90) mri peak = 0.05182 (95) Left_Thalamus (10): linear fit = 1.10 x + 0.0 (2821 voxels, overlap=0.677) Left_Thalamus (10): linear fit = 1.10 x + 0.0 (2821 voxels, peak = 99), gca=98.6 gca peak = 0.11393 (83) mri peak = 0.06507 (88) Right_Thalamus (49): linear fit = 1.04 x + 0.0 (2417 voxels, overlap=0.924) Right_Thalamus (49): linear fit = 1.04 x + 0.0 (2417 voxels, peak = 87), gca=86.7 gca peak = 0.08575 (81) mri peak = 0.09201 (93) Left_Putamen (12): linear fit = 1.12 x + 0.0 (406 voxels, overlap=0.150) Left_Putamen (12): linear fit = 1.12 x + 0.0 (406 voxels, peak = 91), gca=91.1 gca peak = 0.08618 (78) mri peak = 0.06667 (89) Right_Putamen (51): linear fit = 1.11 x + 0.0 (801 voxels, overlap=0.482) Right_Putamen (51): linear fit = 1.11 x + 0.0 (801 voxels, peak = 86), gca=86.2 gca peak = 0.08005 (78) mri peak = 0.07810 (83) Brain_Stem (16): linear fit = 1.09 x + 0.0 (5277 voxels, overlap=0.492) Brain_Stem (16): linear fit = 1.09 x + 0.0 (5277 voxels, peak = 85), gca=84.6 gca peak = 0.12854 (88) mri peak = 0.08155 (95) Right_VentralDC (60): linear fit = 1.10 x + 0.0 (567 voxels, overlap=0.621) Right_VentralDC (60): linear fit = 1.10 x + 0.0 (567 voxels, peak = 96), gca=96.4 gca peak = 0.15703 (87) mri peak = 0.06326 (94) Left_VentralDC (28): linear fit = 1.15 x + 0.0 (460 voxels, overlap=0.252) Left_VentralDC (28): linear fit = 1.15 x + 0.0 (460 voxels, peak = 100), gca=100.5 gca peak = 0.17522 (25) mri peak = 0.11322 (38) gca peak = 0.17113 (14) mri peak = 0.07080 (23) Fourth_Ventricle (15): linear fit = 1.96 x + 0.0 (99 voxels, overlap=0.377) Fourth_Ventricle (15): linear fit = 1.96 x + 0.0 (99 voxels, peak = 27), gca=27.4 gca peak Unknown = 0.94777 ( 0) gca peak Left_Inf_Lat_Vent = 0.16627 (28) gca peak Third_Ventricle = 0.17522 (25) gca peak Fourth_Ventricle = 0.17113 (14) gca peak CSF = 0.20346 (36) gca peak Left_Accumbens_area = 0.70646 (62) gca peak Left_undetermined = 1.00000 (28) gca peak Left_vessel = 0.89917 (53) gca peak Left_choroid_plexus = 0.11689 (35) gca peak Right_Inf_Lat_Vent = 0.25504 (23) gca peak Right_Accumbens_area = 0.31650 (65) gca peak Right_vessel = 0.77268 (52) gca peak Right_choroid_plexus = 0.13275 (38) gca peak Fifth_Ventricle = 0.60973 (33) gca peak WM_hypointensities = 0.11013 (77) gca peak non_WM_hypointensities = 0.11354 (41) gca peak Optic_Chiasm = 0.51646 (76) not using caudate to estimate GM means estimating mean gm scale to be 1.32 x + 0.0 estimating mean wm scale to be 1.01 x + 0.0 estimating mean csf scale to be 1.50 x + 0.0 saving intensity scales to aseg.auto_noCCseg.label_intensities.txt renormalizing by structure alignment.... renormalizing input #0 gca peak = 0.14064 (28) mri peak = 0.08977 (39) Left_Lateral_Ventricle (4): linear fit = 1.26 x + 0.0 (2087 voxels, overlap=0.680) Left_Lateral_Ventricle (4): linear fit = 1.26 x + 0.0 (2087 voxels, peak = 35), gca=35.4 gca peak = 0.16931 (19) mri peak = 0.06346 (28) Right_Lateral_Ventricle (43): linear fit = 1.29 x + 0.0 (1277 voxels, overlap=0.840) Right_Lateral_Ventricle (43): linear fit = 1.29 x + 0.0 (1277 voxels, peak = 25), gca=24.6 gca peak = 0.20916 (101) mri peak = 0.07283 (99) Right_Pallidum (52): linear fit = 1.02 x + 0.0 (347 voxels, overlap=1.019) Right_Pallidum (52): linear fit = 1.02 x + 0.0 (347 voxels, peak = 104), gca=103.5 gca peak = 0.16036 (98) mri peak = 0.06654 (98) Left_Pallidum (13): linear fit = 1.01 x + 0.0 (139 voxels, overlap=0.936) Left_Pallidum (13): linear fit = 1.01 x + 0.0 (139 voxels, peak = 99), gca=99.5 gca peak = 0.25589 (67) mri peak = 0.07964 (67) Right_Hippocampus (53): linear fit = 0.99 x + 0.0 (429 voxels, overlap=1.001) Right_Hippocampus (53): linear fit = 0.99 x + 0.0 (429 voxels, peak = 66), gca=66.0 gca peak = 0.28267 (76) mri peak = 0.10243 (80) Left_Hippocampus (17): linear fit = 0.99 x + 0.0 (381 voxels, overlap=1.001) Left_Hippocampus (17): linear fit = 0.99 x + 0.0 (381 voxels, peak = 75), gca=74.9 gca peak = 0.07890 (105) mri peak = 0.05540 (101) Right_Cerebral_White_Matter (41): linear fit = 1.00 x + 0.0 (41334 voxels, overlap=0.914) Right_Cerebral_White_Matter (41): linear fit = 1.00 x + 0.0 (41334 voxels, peak = 105), gca=105.0 gca peak = 0.07993 (105) mri peak = 0.06051 (102) Left_Cerebral_White_Matter (2): linear fit = 1.00 x + 0.0 (43076 voxels, overlap=0.898) Left_Cerebral_White_Matter (2): linear fit = 1.00 x + 0.0 (43076 voxels, peak = 105), gca=105.0 gca peak = 0.06799 (85) mri peak = 0.04418 (88) Left_Cerebral_Cortex (3): linear fit = 0.99 x + 0.0 (25103 voxels, overlap=0.962) Left_Cerebral_Cortex (3): linear fit = 0.99 x + 0.0 (25103 voxels, peak = 84), gca=83.7 gca peak = 0.08389 (82) mri peak = 0.03911 (80) Right_Cerebral_Cortex (42): linear fit = 0.98 x + 0.0 (24552 voxels, overlap=0.969) Right_Cerebral_Cortex (42): linear fit = 0.98 x + 0.0 (24552 voxels, peak = 80), gca=80.0 gca peak = 0.19535 (86) mri peak = 0.09532 (91) Right_Caudate (50): linear fit = 0.98 x + 0.0 (601 voxels, overlap=1.001) Right_Caudate (50): linear fit = 0.98 x + 0.0 (601 voxels, peak = 84), gca=83.8 gca peak = 0.15917 (88) mri peak = 0.09326 (83) Left_Caudate (11): linear fit = 1.01 x + 0.0 (674 voxels, overlap=0.930) Left_Caudate (11): linear fit = 1.01 x + 0.0 (674 voxels, peak = 89), gca=89.3 gca peak = 0.10357 (73) mri peak = 0.05446 (72) Left_Cerebellum_Cortex (8): linear fit = 1.00 x + 0.0 (9415 voxels, overlap=0.987) Left_Cerebellum_Cortex (8): linear fit = 1.00 x + 0.0 (9415 voxels, peak = 73), gca=73.0 gca peak = 0.12744 (69) mri peak = 0.05719 (67) Right_Cerebellum_Cortex (47): linear fit = 0.99 x + 0.0 (10631 voxels, overlap=0.991) Right_Cerebellum_Cortex (47): linear fit = 0.99 x + 0.0 (10631 voxels, peak = 68), gca=68.0 gca peak = 0.15239 (90) mri peak = 0.06982 (87) Left_Cerebellum_White_Matter (7): linear fit = 0.96 x + 0.0 (4367 voxels, overlap=0.990) Left_Cerebellum_White_Matter (7): linear fit = 0.96 x + 0.0 (4367 voxels, peak = 87), gca=86.8 gca peak = 0.18028 (84) mri peak = 0.06288 (80) Right_Cerebellum_White_Matter (46): linear fit = 1.01 x + 0.0 (4129 voxels, overlap=0.994) Right_Cerebellum_White_Matter (46): linear fit = 1.01 x + 0.0 (4129 voxels, peak = 85), gca=85.3 gca peak = 0.23768 (73) mri peak = 0.08949 (74) Left_Amygdala (18): linear fit = 1.00 x + 0.0 (257 voxels, overlap=0.994) Left_Amygdala (18): linear fit = 1.00 x + 0.0 (257 voxels, peak = 73), gca=73.0 gca peak = 0.31376 (71) mri peak = 0.06418 (65) Right_Amygdala (54): linear fit = 1.03 x + 0.0 (385 voxels, overlap=1.003) Right_Amygdala (54): linear fit = 1.03 x + 0.0 (385 voxels, peak = 73), gca=73.5 gca peak = 0.11163 (97) mri peak = 0.05182 (95) Left_Thalamus (10): linear fit = 1.00 x + 0.0 (2821 voxels, overlap=0.989) Left_Thalamus (10): linear fit = 1.00 x + 0.0 (2821 voxels, peak = 97), gca=97.5 gca peak = 0.09606 (86) mri peak = 0.06507 (88) Right_Thalamus (49): linear fit = 1.01 x + 0.0 (2417 voxels, overlap=0.994) Right_Thalamus (49): linear fit = 1.01 x + 0.0 (2417 voxels, peak = 87), gca=87.3 gca peak = 0.08405 (86) mri peak = 0.09201 (93) Left_Putamen (12): linear fit = 1.02 x + 0.0 (406 voxels, overlap=0.755) Left_Putamen (12): linear fit = 1.02 x + 0.0 (406 voxels, peak = 88), gca=88.2 gca peak = 0.07965 (84) mri peak = 0.06667 (89) Right_Putamen (51): linear fit = 1.00 x + 0.0 (801 voxels, overlap=0.910) Right_Putamen (51): linear fit = 1.00 x + 0.0 (801 voxels, peak = 84), gca=83.6 gca peak = 0.07707 (85) mri peak = 0.07810 (83) Brain_Stem (16): linear fit = 1.02 x + 0.0 (5277 voxels, overlap=0.771) Brain_Stem (16): linear fit = 1.02 x + 0.0 (5277 voxels, peak = 87), gca=87.1 gca peak = 0.11311 (94) mri peak = 0.08155 (95) Right_VentralDC (60): linear fit = 1.00 x + 0.0 (567 voxels, overlap=0.837) Right_VentralDC (60): linear fit = 1.00 x + 0.0 (567 voxels, peak = 94), gca=94.0 gca peak = 0.14756 (99) mri peak = 0.06326 (94) Left_VentralDC (28): linear fit = 1.00 x + 0.0 (460 voxels, overlap=0.946) Left_VentralDC (28): linear fit = 1.00 x + 0.0 (460 voxels, peak = 99), gca=99.5 gca peak = 0.17159 (38) mri peak = 0.11322 (38) gca peak = 0.15149 (22) mri peak = 0.07080 (23) Fourth_Ventricle (15): linear fit = 1.27 x + 0.0 (99 voxels, overlap=0.773) Fourth_Ventricle (15): linear fit = 1.27 x + 0.0 (99 voxels, peak = 28), gca=28.0 gca peak Unknown = 0.94777 ( 0) gca peak Left_Inf_Lat_Vent = 0.15275 (37) gca peak Third_Ventricle = 0.17159 (38) gca peak CSF = 0.13119 (54) gca peak Left_Accumbens_area = 0.46411 (71) gca peak Left_undetermined = 0.98480 (34) gca peak Left_vessel = 0.63642 (53) gca peak Left_choroid_plexus = 0.11039 (35) gca peak Right_Inf_Lat_Vent = 0.26261 (28) gca peak Right_Accumbens_area = 0.30641 (84) gca peak Right_vessel = 0.77268 (52) gca peak Right_choroid_plexus = 0.13879 (38) gca peak Fifth_Ventricle = 0.59466 (47) gca peak WM_hypointensities = 0.10602 (77) gca peak non_WM_hypointensities = 0.14199 (41) gca peak Optic_Chiasm = 0.51650 (76) not using caudate to estimate GM means estimating mean gm scale to be 0.99 x + 0.0 estimating mean wm scale to be 1.00 x + 0.0 estimating mean csf scale to be 1.28 x + 0.0 Right_Pallidum too bright - rescaling by 0.984 (from 1.025) to 101.8 (was 103.5) saving intensity scales to aseg.auto_noCCseg.label_intensities.txt saving sequentially combined intensity scales to aseg.auto_noCCseg.label_intensities.txt 158610 voxels changed in iteration 0 of unlikely voxel relabeling 219 voxels changed in iteration 1 of unlikely voxel relabeling 2 voxels changed in iteration 2 of unlikely voxel relabeling 0 voxels changed in iteration 3 of unlikely voxel relabeling 176344 gm and wm labels changed (%32 to gray, %68 to white out of all changed labels) 776 hippocampal voxels changed. 1 amygdala voxels changed. Reclassifying using Gibbs Priors pass 1: 151868 changed. image ll: -2.214, PF=0.500 pass 2: 40042 changed. image ll: -2.210, PF=0.500 pass 3: 11067 changed. pass 4: 3806 changed. 142590 voxels changed in iteration 0 of unlikely voxel relabeling 1013 voxels changed in iteration 1 of unlikely voxel relabeling 53 voxels changed in iteration 2 of unlikely voxel relabeling 1 voxels changed in iteration 3 of unlikely voxel relabeling 0 voxels changed in iteration 4 of unlikely voxel relabeling 9627 voxels changed in iteration 0 of unlikely voxel relabeling 206 voxels changed in iteration 1 of unlikely voxel relabeling 2 voxels changed in iteration 2 of unlikely voxel relabeling 0 voxels changed in iteration 3 of unlikely voxel relabeling 7026 voxels changed in iteration 0 of unlikely voxel relabeling 111 voxels changed in iteration 1 of unlikely voxel relabeling 5 voxels changed in iteration 2 of unlikely voxel relabeling 6 voxels changed in iteration 3 of unlikely voxel relabeling 0 voxels changed in iteration 4 of unlikely voxel relabeling 5892 voxels changed in iteration 0 of unlikely voxel relabeling 67 voxels changed in iteration 1 of unlikely voxel relabeling 0 voxels changed in iteration 2 of unlikely voxel relabeling !!!!!!!!! ventricle segment 1 with volume 13222 above threshold 100 - not erasing !!!!!!!!!! !!!!!!!!! ventricle segment 0 with volume 158 above threshold 100 - not erasing !!!!!!!!!! !!!!!!!!! ventricle segment 1 with volume 8734 above threshold 100 - not erasing !!!!!!!!!! !!!!!!!!! ventricle segment 5 with volume 360 above threshold 100 - not erasing !!!!!!!!!! writing labeled volume to aseg.auto_noCCseg.mgz mri_ca_label utimesec 3337.188108 mri_ca_label stimesec 0.883989 mri_ca_label ru_maxrss 2118284 mri_ca_label ru_ixrss 0 mri_ca_label ru_idrss 0 mri_ca_label ru_isrss 0 mri_ca_label ru_minflt 1079762 mri_ca_label ru_majflt 7 mri_ca_label ru_nswap 0 mri_ca_label ru_inblock 2152 mri_ca_label ru_oublock 784 mri_ca_label ru_msgsnd 0 mri_ca_label ru_msgrcv 0 mri_ca_label ru_nsignals 0 mri_ca_label ru_nvcsw 261 mri_ca_label ru_nivcsw 9830 auto-labeling took 54 minutes and 37 seconds. @#@FSTIME 2021:11:09:18:35:59 mri_ca_label N 10 e 3276.90 S 0.93 U 3337.18 P 101% M 2118284 F 7 R 1079764 W 0 c 9831 w 262 I 2152 O 784 L 3.35 3.14 2.96 @#@FSLOADPOST 2021:11:09:19:30:36 mri_ca_label N 10 1.00 1.00 1.03 #-------------------------------------- #@# CC Seg Tue Nov 9 19:30:36 EST 2021 mri_cc -aseg aseg.auto_noCCseg.mgz -o aseg.auto.mgz -lta /home/basuia/Documents/mmvt_root/subjects/UC07/mri/transforms/cc_up.lta UC07 will read input aseg from aseg.auto_noCCseg.mgz writing aseg with cc labels to aseg.auto.mgz will write lta as /home/basuia/Documents/mmvt_root/subjects/UC07/mri/transforms/cc_up.lta reading aseg from /home/basuia/Documents/mmvt_root/subjects/UC07/mri/aseg.auto_noCCseg.mgz reading norm from /home/basuia/Documents/mmvt_root/subjects/UC07/mri/norm.mgz MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab 34077 voxels in left wm, 70299 in right wm, xrange [126, 135] searching rotation angles z=[-9 5], y=[-8 6] searching scale 1 Z rot -8.9 searching scale 1 Z rot -8.7 searching scale 1 Z rot -8.4 searching scale 1 Z rot -8.2 searching scale 1 Z rot -7.9 searching scale 1 Z rot -7.7 searching scale 1 Z rot -7.4 searching scale 1 Z rot -7.2 searching scale 1 Z rot -6.9 searching scale 1 Z rot -6.7 searching scale 1 Z rot -6.4 searching scale 1 Z rot -6.2 searching scale 1 Z rot -5.9 searching scale 1 Z rot -5.7 searching scale 1 Z rot -5.4 searching scale 1 Z rot -5.2 searching scale 1 Z rot -4.9 searching scale 1 Z rot -4.7 searching scale 1 Z rot -4.4 searching scale 1 Z rot -4.2 searching scale 1 Z rot -3.9 searching scale 1 Z rot -3.7 searching scale 1 Z rot -3.4 searching scale 1 Z rot -3.2 searching scale 1 Z rot -2.9 searching scale 1 Z rot -2.7 searching scale 1 Z rot -2.4 searching scale 1 Z rot -2.2 searching scale 1 Z rot -1.9 searching scale 1 Z rot -1.7 searching scale 1 Z rot -1.4 searching scale 1 Z rot -1.2 searching scale 1 Z rot -0.9 searching scale 1 Z rot -0.7 searching scale 1 Z rot -0.4 searching scale 1 Z rot -0.2 searching scale 1 Z rot 0.1 searching scale 1 Z rot 0.3 searching scale 1 Z rot 0.6 searching scale 1 Z rot 0.8 searching scale 1 Z rot 1.1 searching scale 1 Z rot 1.3 searching scale 1 Z rot 1.6 searching scale 1 Z rot 1.8 searching scale 1 Z rot 2.1 searching scale 1 Z rot 2.3 searching scale 1 Z rot 2.6 searching scale 1 Z rot 2.8 searching scale 1 Z rot 3.1 searching scale 1 Z rot 3.3 searching scale 1 Z rot 3.6 searching scale 1 Z rot 3.8 searching scale 1 Z rot 4.1 searching scale 1 Z rot 4.3 searching scale 1 Z rot 4.6 searching scale 1 Z rot 4.8 global minimum found at slice 131.6, rotations (-1.18, -1.93) final transformation (x=131.6, yr=-1.183, zr=-1.930): 0.99922 0.03368 -0.02063 -4.94809; -0.03367 0.99943 0.00070 20.41638; 0.02064 0.00000 0.99979 14.30766; 0.00000 0.00000 0.00000 1.00000; updating x range to be [125, 131] in xformed coordinates best xformed slice 127 min_x_fornix = 128 min_x_fornix = 131 min_x_fornix = 136 min_x_fornix = 133 min_x_fornix = 132 cc center is found at 127 112 111 eigenvectors: 0.00096 -0.00161 1.00000; 0.01389 -0.99990 -0.00162; 0.99990 0.01389 -0.00093; MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab writing aseg with callosum to /home/basuia/Documents/mmvt_root/subjects/UC07/mri/aseg.auto.mgz... corpus callosum segmentation took 0.8 minutes #VMPC# mri_cc VmPeak 478132 mri_cc done @#@FSTIME 2021:11:09:19:30:36 mri_cc N 7 e 48.90 S 0.22 U 49.60 P 101% M 343508 F 4 R 277871 W 0 c 143 w 26 I 960 O 768 L 1.00 1.00 1.03 @#@FSLOADPOST 2021:11:09:19:31:25 mri_cc N 7 1.00 1.00 1.03 #-------------------------------------- #@# Merge ASeg Tue Nov 9 19:31:25 EST 2021 cp aseg.auto.mgz aseg.presurf.mgz #-------------------------------------------- #@# Intensity Normalization2 Tue Nov 9 19:31:25 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/mri mri_normalize -seed 1234 -mprage -aseg aseg.presurf.mgz -mask brainmask.mgz norm.mgz brain.mgz setting seed for random number genererator to 1234 assuming input volume is MGH (Van der Kouwe) MP-RAGE using segmentation for initial intensity normalization using MR volume brainmask.mgz to mask input volume... reading mri_src from norm.mgz... Reading aseg aseg.presurf.mgz normalizing image... NOT doing gentle normalization with control points/label processing with aseg MRIcopyHeader(): source has ctab removing outliers in the aseg WM... MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab 4430 control points removed MRIcopyHeader(): source has ctab Building bias image building Voronoi diagram... performing soap bubble smoothing, sigma = 0... Smoothing with sigma 8 Applying bias correction building Voronoi diagram... performing soap bubble smoothing, sigma = 8... Iterating 2 times --------------------------------- 3d normalization pass 1 of 2 white matter peak found at 110 white matter peak found at 90 gm peak at 68 (68), valley at 20 (20) csf peak at 35, setting threshold to 57 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... --------------------------------- 3d normalization pass 2 of 2 white matter peak found at 110 white matter peak found at 89 gm peak at 67 (67), valley at 19 (19) csf peak at 34, setting threshold to 56 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... Done iterating --------------------------------- writing output to brain.mgz 3D bias adjustment took 1 minutes and 56 seconds. @#@FSTIME 2021:11:09:19:31:25 mri_normalize N 9 e 117.41 S 0.70 U 131.23 P 112% M 1202772 F 0 R 632698 W 0 c 330 w 25 I 0 O 3184 L 1.00 1.00 1.03 @#@FSLOADPOST 2021:11:09:19:33:22 mri_normalize N 9 1.00 1.00 1.02 #-------------------------------------------- #@# Mask BFS Tue Nov 9 19:33:22 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/mri mri_mask -T 5 brain.mgz brainmask.mgz brain.finalsurfs.mgz threshold mask volume at 5 DoAbs = 0 Found 1795247 voxels in mask (pct= 10.70) Writing masked volume to brain.finalsurfs.mgz...done. @#@FSTIME 2021:11:09:19:33:22 mri_mask N 5 e 0.76 S 0.00 U 1.30 P 170% M 74176 F 4 R 17278 W 0 c 1 w 11 I 984 O 3128 L 1.00 1.00 1.02 @#@FSLOADPOST 2021:11:09:19:33:23 mri_mask N 5 1.00 1.00 1.02 #-------------------------------------------- #@# WM Segmentation Tue Nov 9 19:33:23 EST 2021 AntsDenoiseImageFs -i brain.mgz -o antsdn.brain.mgz @#@FSTIME 2021:11:09:19:33:23 AntsDenoiseImageFs N 4 e 56.27 S 0.09 U 56.45 P 100% M 350712 F 20 R 86510 W 0 c 248 w 25 I 4240 O 3136 L 1.00 1.00 1.02 @#@FSLOADPOST 2021:11:09:19:34:19 AntsDenoiseImageFs N 4 1.00 1.00 1.01 mri_segment -wsizemm 13 -mprage antsdn.brain.mgz wm.seg.mgz wsizemm = 13, voxres = 1, wsize = 13 Widening wm low from 89 to 79 assuming input volume is MGH (Van der Kouwe) MP-RAGE wm mean: 110 wsize: 13 wm low: 79 wm hi: 125 gray low: 30 gray hi: 99 Doing initial trinary intensity segmentation Using local statistics to label ambiguous voxels Autodetecting stats Computing class statistics for intensity windows... CCS WM (100.0): 99.9 +- 5.9 [79.0 --> 125.0] CCS GM (79.0) : 77.0 +- 11.2 [30.0 --> 95.0] white_mean 99.9314 white_sigma 5.92256 gray_mean 76.9959 gray_sigma 11.2087 setting bottom of white matter range wm_low to 88.2 setting top of gray matter range gray_hi to 99.4 wm_low 88.2046 wm_hi 125 gray_low 30 gray_hi 99.4132 Redoing initial intensity segmentation... Recomputing local statistics to label ambiguous voxels... wm_low 88.2046 wm_hi 125 gray_low 30 gray_hi 99.4132 using local geometry to label remaining ambiguous voxels... polvwsize = 5, polvlen = 3, gray_hi = 99.4132, wm_low = 88.2046 MRIcpolvMedianCurveSegment(): wsize=5, len=3, gmhi=99.4132, wmlow=88.2046 260802 voxels processed (1.55%) 121407 voxels white (0.72%) 139395 voxels non-white (0.83%) Reclassifying voxels using Gaussian border classifier niter=1 MRIreclassify(): wm_low=83.2046, gray_hi=99.4132, wsize=13 504267 voxels tested (3.01%) 98725 voxels changed (0.59%) 88947 multi-scale searches (0.53%) Recovering bright white MRIrecoverBrightWhite() wm_low 88.2046 wm_hi 125 slack 5.92256 pct_thresh 0.33 intensity_thresh 130.923 nvox_thresh 8.58 83 voxels tested (0.00%) 45 voxels changed (0.00%) removing voxels with positive offset direction... MRIremoveWrongDirection() wsize=3, lowthr=83.2046, hithr=99.4132 smoothing input volume with sigma = 0.250 241497 voxels tested (1.44%) 41608 voxels changed (0.25%) thicken = 1 removing 1-dimensional structures... MRIremove1dStructures(): max_iter=10000, thresh=2, WM_MIN_VAL=5 11055 sparsely connected voxels removed in 1 iterations thickening thin strands.... thickness 4 nsegments 20 wm_hi 125 10249 diagonally connected voxels added... MRIthickenThinWMStrands(): thickness=4, nsegments=20 20 segments, 4686 filled MRIfindBrightNonWM(): 384 bright non-wm voxels segmented. MRIfilterMorphology() WM_MIN_VAL=5, DIAGONAL_FILL=230 white matter segmentation took 1.8 minutes writing output to wm.seg.mgz... @#@FSTIME 2021:11:09:19:34:19 mri_segment N 5 e 109.90 S 0.23 U 110.49 P 100% M 149540 F 3 R 299407 W 0 c 284 w 13 I 768 O 1032 L 1.00 1.00 1.01 @#@FSLOADPOST 2021:11:09:19:36:09 mri_segment N 5 1.00 1.00 1.00 mri_edit_wm_with_aseg -keep-in wm.seg.mgz brain.mgz aseg.presurf.mgz wm.asegedit.mgz preserving editing changes in input volume... auto filling took 0.42 minutes reading wm segmentation from wm.seg.mgz... MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab 0 voxels added to wm to prevent paths from MTL structures to cortex 12697 additional wm voxels added 0 additional wm voxels added SEG EDIT: 87743 voxels turned on, 17268 voxels turned off. propagating editing to output volume from wm.seg.mgz writing edited volume to wm.asegedit.mgz.... @#@FSTIME 2021:11:09:19:36:09 mri_edit_wm_with_aseg N 5 e 25.18 S 0.19 U 26.85 P 107% M 462164 F 4 R 317160 W 0 c 83 w 47 I 992 O 1000 L 1.00 1.00 1.00 @#@FSLOADPOST 2021:11:09:19:36:35 mri_edit_wm_with_aseg N 5 1.00 1.00 1.00 mri_pretess wm.asegedit.mgz wm norm.mgz wm.mgz Iteration Number : 1 pass 1 (xy+): 61 found - 61 modified | TOTAL: 61 pass 2 (xy+): 0 found - 61 modified | TOTAL: 61 pass 1 (xy-): 69 found - 69 modified | TOTAL: 130 pass 2 (xy-): 0 found - 69 modified | TOTAL: 130 pass 1 (yz+): 91 found - 91 modified | TOTAL: 221 pass 2 (yz+): 0 found - 91 modified | TOTAL: 221 pass 1 (yz-): 70 found - 70 modified | TOTAL: 291 pass 2 (yz-): 0 found - 70 modified | TOTAL: 291 pass 1 (xz+): 89 found - 89 modified | TOTAL: 380 pass 2 (xz+): 0 found - 89 modified | TOTAL: 380 pass 1 (xz-): 77 found - 77 modified | TOTAL: 457 pass 2 (xz-): 0 found - 77 modified | TOTAL: 457 Iteration Number : 1 pass 1 (+++): 62 found - 62 modified | TOTAL: 62 pass 2 (+++): 0 found - 62 modified | TOTAL: 62 pass 1 (+++): 69 found - 69 modified | TOTAL: 131 pass 2 (+++): 0 found - 69 modified | TOTAL: 131 pass 1 (+++): 75 found - 75 modified | TOTAL: 206 pass 2 (+++): 0 found - 75 modified | TOTAL: 206 pass 1 (+++): 95 found - 95 modified | TOTAL: 301 pass 2 (+++): 0 found - 95 modified | TOTAL: 301 Iteration Number : 1 pass 1 (++): 294 found - 294 modified | TOTAL: 294 pass 2 (++): 0 found - 294 modified | TOTAL: 294 pass 1 (+-): 310 found - 310 modified | TOTAL: 604 pass 2 (+-): 0 found - 310 modified | TOTAL: 604 pass 1 (--): 291 found - 291 modified | TOTAL: 895 pass 2 (--): 1 found - 292 modified | TOTAL: 896 pass 3 (--): 0 found - 292 modified | TOTAL: 896 pass 1 (-+): 285 found - 285 modified | TOTAL: 1181 pass 2 (-+): 0 found - 285 modified | TOTAL: 1181 Iteration Number : 2 pass 1 (xy+): 31 found - 31 modified | TOTAL: 31 pass 2 (xy+): 0 found - 31 modified | TOTAL: 31 pass 1 (xy-): 32 found - 32 modified | TOTAL: 63 pass 2 (xy-): 0 found - 32 modified | TOTAL: 63 pass 1 (yz+): 27 found - 27 modified | TOTAL: 90 pass 2 (yz+): 0 found - 27 modified | TOTAL: 90 pass 1 (yz-): 42 found - 42 modified | TOTAL: 132 pass 2 (yz-): 0 found - 42 modified | TOTAL: 132 pass 1 (xz+): 33 found - 33 modified | TOTAL: 165 pass 2 (xz+): 0 found - 33 modified | TOTAL: 165 pass 1 (xz-): 34 found - 34 modified | TOTAL: 199 pass 2 (xz-): 0 found - 34 modified | TOTAL: 199 Iteration Number : 2 pass 1 (+++): 3 found - 3 modified | TOTAL: 3 pass 2 (+++): 0 found - 3 modified | TOTAL: 3 pass 1 (+++): 11 found - 11 modified | TOTAL: 14 pass 2 (+++): 0 found - 11 modified | TOTAL: 14 pass 1 (+++): 4 found - 4 modified | TOTAL: 18 pass 2 (+++): 0 found - 4 modified | TOTAL: 18 pass 1 (+++): 2 found - 2 modified | TOTAL: 20 pass 2 (+++): 0 found - 2 modified | TOTAL: 20 Iteration Number : 2 pass 1 (++): 18 found - 18 modified | TOTAL: 18 pass 2 (++): 0 found - 18 modified | TOTAL: 18 pass 1 (+-): 12 found - 12 modified | TOTAL: 30 pass 2 (+-): 0 found - 12 modified | TOTAL: 30 pass 1 (--): 17 found - 17 modified | TOTAL: 47 pass 2 (--): 0 found - 17 modified | TOTAL: 47 pass 1 (-+): 12 found - 12 modified | TOTAL: 59 pass 2 (-+): 0 found - 12 modified | TOTAL: 59 Iteration Number : 3 pass 1 (xy+): 4 found - 4 modified | TOTAL: 4 pass 2 (xy+): 0 found - 4 modified | TOTAL: 4 pass 1 (xy-): 0 found - 0 modified | TOTAL: 4 pass 1 (yz+): 6 found - 6 modified | TOTAL: 10 pass 2 (yz+): 0 found - 6 modified | TOTAL: 10 pass 1 (yz-): 6 found - 6 modified | TOTAL: 16 pass 2 (yz-): 0 found - 6 modified | TOTAL: 16 pass 1 (xz+): 1 found - 1 modified | TOTAL: 17 pass 2 (xz+): 0 found - 1 modified | TOTAL: 17 pass 1 (xz-): 0 found - 0 modified | TOTAL: 17 Iteration Number : 3 pass 1 (+++): 1 found - 1 modified | TOTAL: 1 pass 2 (+++): 0 found - 1 modified | TOTAL: 1 pass 1 (+++): 0 found - 0 modified | TOTAL: 1 pass 1 (+++): 0 found - 0 modified | TOTAL: 1 pass 1 (+++): 2 found - 2 modified | TOTAL: 3 pass 2 (+++): 0 found - 2 modified | TOTAL: 3 Iteration Number : 3 pass 1 (++): 1 found - 1 modified | TOTAL: 1 pass 2 (++): 0 found - 1 modified | TOTAL: 1 pass 1 (+-): 0 found - 0 modified | TOTAL: 1 pass 1 (--): 1 found - 1 modified | TOTAL: 2 pass 2 (--): 0 found - 1 modified | TOTAL: 2 pass 1 (-+): 2 found - 2 modified | TOTAL: 4 pass 2 (-+): 0 found - 2 modified | TOTAL: 4 Iteration Number : 4 pass 1 (xy+): 1 found - 1 modified | TOTAL: 1 pass 2 (xy+): 0 found - 1 modified | TOTAL: 1 pass 1 (xy-): 0 found - 0 modified | TOTAL: 1 pass 1 (yz+): 0 found - 0 modified | TOTAL: 1 pass 1 (yz-): 0 found - 0 modified | TOTAL: 1 pass 1 (xz+): 1 found - 1 modified | TOTAL: 2 pass 2 (xz+): 0 found - 1 modified | TOTAL: 2 pass 1 (xz-): 1 found - 1 modified | TOTAL: 3 pass 2 (xz-): 0 found - 1 modified | TOTAL: 3 Iteration Number : 4 pass 1 (+++): 2 found - 2 modified | TOTAL: 2 pass 2 (+++): 0 found - 2 modified | TOTAL: 2 pass 1 (+++): 0 found - 0 modified | TOTAL: 2 pass 1 (+++): 0 found - 0 modified | TOTAL: 2 pass 1 (+++): 0 found - 0 modified | TOTAL: 2 Iteration Number : 4 pass 1 (++): 0 found - 0 modified | TOTAL: 0 pass 1 (+-): 1 found - 1 modified | TOTAL: 1 pass 2 (+-): 0 found - 1 modified | TOTAL: 1 pass 1 (--): 0 found - 0 modified | TOTAL: 1 pass 1 (-+): 0 found - 0 modified | TOTAL: 1 Iteration Number : 5 pass 1 (xy+): 0 found - 0 modified | TOTAL: 0 pass 1 (xy-): 0 found - 0 modified | TOTAL: 0 pass 1 (yz+): 0 found - 0 modified | TOTAL: 0 pass 1 (yz-): 0 found - 0 modified | TOTAL: 0 pass 1 (xz+): 0 found - 0 modified | TOTAL: 0 pass 1 (xz-): 0 found - 0 modified | TOTAL: 0 Iteration Number : 5 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 Iteration Number : 5 pass 1 (++): 0 found - 0 modified | TOTAL: 0 pass 1 (+-): 0 found - 0 modified | TOTAL: 0 pass 1 (--): 0 found - 0 modified | TOTAL: 0 pass 1 (-+): 0 found - 0 modified | TOTAL: 0 Total Number of Modified Voxels = 2247 (out of 604338: 0.371812) binarizing input wm segmentation... Ambiguous edge configurations... mri_pretess done @#@FSTIME 2021:11:09:19:36:35 mri_pretess N 4 e 3.28 S 0.00 U 3.80 P 116% M 56740 F 16 R 12982 W 0 c 11 w 24 I 3568 O 1000 L 1.00 1.00 1.00 @#@FSLOADPOST 2021:11:09:19:36:38 mri_pretess N 4 1.00 1.00 1.00 #-------------------------------------------- #@# Fill Tue Nov 9 19:36:38 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/mri mri_fill -a ../scripts/ponscc.cut.log -xform transforms/talairach.lta -segmentation aseg.presurf.mgz -ctab /home/basuia/Documents/mmvt_root/freesurfer/SubCorticalMassLUT.txt wm.mgz filled.mgz logging cutting plane coordinates to ../scripts/ponscc.cut.log... INFO: Using transforms/talairach.lta and its offset for Talairach volume ... using segmentation aseg.presurf.mgz... reading input volume...done. searching for cutting planes...voxel to talairach voxel transform 1.03341 0.08993 0.03566 -25.58376; -0.10320 0.96366 0.12473 -8.61546; -0.02584 -0.12726 0.92802 24.18417; 0.00000 0.00000 0.00000 1.00000; voxel to talairach voxel transform 1.03341 0.08993 0.03566 -25.58376; -0.10320 0.96366 0.12473 -8.61546; -0.02584 -0.12726 0.92802 24.18417; 0.00000 0.00000 0.00000 1.00000; reading segmented volume aseg.presurf.mgz removing CC from segmentation MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab Looking for area (min, max) = (350, 1400) area[0] = 1118 (min = 350, max = 1400), aspect = 0.39 (min = 0.10, max = 0.75) no need to search using seed (127, 121, 150), TAL = (1.0, 22.0, 7.0) talairach voxel to voxel transform 0.95781 -0.09260 -0.02436 24.29578; 0.09739 1.01019 -0.13952 14.56907; 0.04003 0.13595 1.05775 -23.38553; 0.00000 0.00000 0.00000 1.00000; segmentation indicates cc at (127, 121, 150) --> (1.0, 22.0, 7.0) done. filling took 1.1 minutes talairach cc position changed to (1.00, 22.00, 7.00) Erasing brainstem...done. seed_search_size = 9, min_neighbors = 5 search rh wm seed point around talairach space:(19.00, 22.00, 7.00) SRC: (113.84, 126.49, 156.09) search lh wm seed point around talairach space (-17.00, 22.00, 7.00), SRC: (148.32, 130.00, 157.53) compute mri_fill using aseg Erasing Brain Stem and Cerebellum ... Define left and right masks using aseg: Building Voronoi diagram ... Using the Voronoi diagram for separating WM into two hemispheres ... Find the largest connected component for each hemisphere ... Embedding colortable mri_fill done, writing output to filled.mgz... @#@FSTIME 2021:11:09:19:36:38 mri_fill N 10 e 67.71 S 0.65 U 67.70 P 100% M 1013712 F 4 R 527669 W 0 c 227 w 12 I 1280 O 312 L 1.00 1.00 1.00 @#@FSLOADPOST 2021:11:09:19:37:46 mri_fill N 10 1.00 1.00 1.00 cp filled.mgz filled.auto.mgz #-------------------------------------------- #@# Tessellate lh Tue Nov 9 19:37:46 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/scripts mri_pretess ../mri/filled.mgz 255 ../mri/norm.mgz ../mri/filled-pretess255.mgz Iteration Number : 1 pass 1 (xy+): 8 found - 8 modified | TOTAL: 8 pass 2 (xy+): 0 found - 8 modified | TOTAL: 8 pass 1 (xy-): 4 found - 4 modified | TOTAL: 12 pass 2 (xy-): 0 found - 4 modified | TOTAL: 12 pass 1 (yz+): 14 found - 14 modified | TOTAL: 26 pass 2 (yz+): 0 found - 14 modified | TOTAL: 26 pass 1 (yz-): 7 found - 7 modified | TOTAL: 33 pass 2 (yz-): 0 found - 7 modified | TOTAL: 33 pass 1 (xz+): 3 found - 3 modified | TOTAL: 36 pass 2 (xz+): 0 found - 3 modified | TOTAL: 36 pass 1 (xz-): 1 found - 1 modified | TOTAL: 37 pass 2 (xz-): 0 found - 1 modified | TOTAL: 37 Iteration Number : 1 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 Iteration Number : 1 pass 1 (++): 0 found - 0 modified | TOTAL: 0 pass 1 (+-): 3 found - 3 modified | TOTAL: 3 pass 2 (+-): 0 found - 3 modified | TOTAL: 3 pass 1 (--): 5 found - 5 modified | TOTAL: 8 pass 2 (--): 0 found - 5 modified | TOTAL: 8 pass 1 (-+): 5 found - 5 modified | TOTAL: 13 pass 2 (-+): 0 found - 5 modified | TOTAL: 13 Iteration Number : 2 pass 1 (xy+): 0 found - 0 modified | TOTAL: 0 pass 1 (xy-): 0 found - 0 modified | TOTAL: 0 pass 1 (yz+): 0 found - 0 modified | TOTAL: 0 pass 1 (yz-): 0 found - 0 modified | TOTAL: 0 pass 1 (xz+): 0 found - 0 modified | TOTAL: 0 pass 1 (xz-): 1 found - 1 modified | TOTAL: 1 pass 2 (xz-): 0 found - 1 modified | TOTAL: 1 Iteration Number : 2 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 Iteration Number : 2 pass 1 (++): 0 found - 0 modified | TOTAL: 0 pass 1 (+-): 0 found - 0 modified | TOTAL: 0 pass 1 (--): 0 found - 0 modified | TOTAL: 0 pass 1 (-+): 1 found - 1 modified | TOTAL: 1 pass 2 (-+): 0 found - 1 modified | TOTAL: 1 Iteration Number : 3 pass 1 (xy+): 0 found - 0 modified | TOTAL: 0 pass 1 (xy-): 0 found - 0 modified | TOTAL: 0 pass 1 (yz+): 0 found - 0 modified | TOTAL: 0 pass 1 (yz-): 0 found - 0 modified | TOTAL: 0 pass 1 (xz+): 0 found - 0 modified | TOTAL: 0 pass 1 (xz-): 0 found - 0 modified | TOTAL: 0 Iteration Number : 3 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 Iteration Number : 3 pass 1 (++): 0 found - 0 modified | TOTAL: 0 pass 1 (+-): 0 found - 0 modified | TOTAL: 0 pass 1 (--): 0 found - 0 modified | TOTAL: 0 pass 1 (-+): 0 found - 0 modified | TOTAL: 0 Total Number of Modified Voxels = 52 (out of 311742: 0.016680) Ambiguous edge configurations... mri_pretess done @#@FSTIME 2021:11:09:19:37:46 mri_pretess N 4 e 1.46 S 0.00 U 1.99 P 136% M 40464 F 0 R 8856 W 0 c 3 w 7 I 0 O 304 L 1.00 1.00 1.00 @#@FSLOADPOST 2021:11:09:19:37:47 mri_pretess N 4 1.00 1.00 1.00 mri_tessellate ../mri/filled-pretess255.mgz 255 ../surf/lh.orig.nofix dev dev slice 30: 214 vertices, 248 faces slice 40: 4588 vertices, 4769 faces slice 50: 13213 vertices, 13573 faces slice 60: 23674 vertices, 24111 faces slice 70: 36865 vertices, 37302 faces slice 80: 50269 vertices, 50750 faces slice 90: 63217 vertices, 63681 faces slice 100: 76904 vertices, 77450 faces slice 110: 90761 vertices, 91381 faces slice 120: 103774 vertices, 104354 faces slice 130: 114746 vertices, 115364 faces slice 140: 124281 vertices, 124898 faces slice 150: 132466 vertices, 133053 faces slice 160: 141055 vertices, 141700 faces slice 170: 148560 vertices, 149155 faces slice 180: 154781 vertices, 155352 faces slice 190: 160086 vertices, 160622 faces slice 200: 163037 vertices, 163499 faces slice 210: 163322 vertices, 163720 faces slice 220: 163322 vertices, 163720 faces slice 230: 163322 vertices, 163720 faces slice 240: 163322 vertices, 163720 faces slice 250: 163322 vertices, 163720 faces using the conformed surface RAS to save vertex points... writing ../surf/lh.orig.nofix using vox2ras matrix: -1.00000 0.00000 0.00000 128.00000; 0.00000 0.00000 1.00000 -128.00000; 0.00000 -1.00000 0.00000 128.00000; 0.00000 0.00000 0.00000 1.00000; @#@FSTIME 2021:11:09:19:37:47 mri_tessellate N 3 e 1.09 S 0.00 U 1.35 P 124% M 40052 F 3 R 9010 W 0 c 3 w 8 I 1184 O 7672 L 1.00 1.00 1.00 @#@FSLOADPOST 2021:11:09:19:37:48 mri_tessellate N 3 1.00 1.00 1.00 rm -f ../mri/filled-pretess255.mgz mris_extract_main_component ../surf/lh.orig.nofix ../surf/lh.orig.nofix counting number of connected components... 163290 voxel in cpt #1: X=-402 [v=163290,e=491076,f=327384] located at (-31.274818, -22.144020, 5.279490) 20 voxel in cpt #2: X=2 [v=20,e=54,f=36] located at (-5.500000, 4.000000, 16.000000) 12 voxel in cpt #3: X=2 [v=12,e=30,f=20] located at (-4.500000, 19.000000, 9.000000) For the whole surface: X=-398 [v=163322,e=491160,f=327440] 3 components have been found keeping component #1 with 163290 vertices done @#@FSTIME 2021:11:09:19:37:48 mris_extract_main_component N 2 e 0.79 S 0.08 U 1.03 P 140% M 324336 F 14 R 86159 W 0 c 3 w 26 I 3264 O 11504 L 1.00 1.00 1.00 @#@FSLOADPOST 2021:11:09:19:37:49 mris_extract_main_component N 2 1.00 1.00 1.00 #-------------------------------------------- #@# Tessellate rh Tue Nov 9 19:37:49 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/scripts mri_pretess ../mri/filled.mgz 127 ../mri/norm.mgz ../mri/filled-pretess127.mgz Iteration Number : 1 pass 1 (xy+): 0 found - 0 modified | TOTAL: 0 pass 1 (xy-): 1 found - 1 modified | TOTAL: 1 pass 2 (xy-): 0 found - 1 modified | TOTAL: 1 pass 1 (yz+): 13 found - 13 modified | TOTAL: 14 pass 2 (yz+): 0 found - 13 modified | TOTAL: 14 pass 1 (yz-): 13 found - 13 modified | TOTAL: 27 pass 2 (yz-): 0 found - 13 modified | TOTAL: 27 pass 1 (xz+): 2 found - 2 modified | TOTAL: 29 pass 2 (xz+): 0 found - 2 modified | TOTAL: 29 pass 1 (xz-): 1 found - 1 modified | TOTAL: 30 pass 2 (xz-): 0 found - 1 modified | TOTAL: 30 Iteration Number : 1 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 1 found - 1 modified | TOTAL: 1 pass 2 (+++): 0 found - 1 modified | TOTAL: 1 pass 1 (+++): 2 found - 2 modified | TOTAL: 3 pass 2 (+++): 0 found - 2 modified | TOTAL: 3 Iteration Number : 1 pass 1 (++): 0 found - 0 modified | TOTAL: 0 pass 1 (+-): 2 found - 2 modified | TOTAL: 2 pass 2 (+-): 0 found - 2 modified | TOTAL: 2 pass 1 (--): 2 found - 2 modified | TOTAL: 4 pass 2 (--): 0 found - 2 modified | TOTAL: 4 pass 1 (-+): 1 found - 1 modified | TOTAL: 5 pass 2 (-+): 0 found - 1 modified | TOTAL: 5 Iteration Number : 2 pass 1 (xy+): 0 found - 0 modified | TOTAL: 0 pass 1 (xy-): 0 found - 0 modified | TOTAL: 0 pass 1 (yz+): 1 found - 1 modified | TOTAL: 1 pass 2 (yz+): 0 found - 1 modified | TOTAL: 1 pass 1 (yz-): 0 found - 0 modified | TOTAL: 1 pass 1 (xz+): 0 found - 0 modified | TOTAL: 1 pass 1 (xz-): 0 found - 0 modified | TOTAL: 1 Iteration Number : 2 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 Iteration Number : 2 pass 1 (++): 0 found - 0 modified | TOTAL: 0 pass 1 (+-): 0 found - 0 modified | TOTAL: 0 pass 1 (--): 0 found - 0 modified | TOTAL: 0 pass 1 (-+): 0 found - 0 modified | TOTAL: 0 Iteration Number : 3 pass 1 (xy+): 0 found - 0 modified | TOTAL: 0 pass 1 (xy-): 0 found - 0 modified | TOTAL: 0 pass 1 (yz+): 0 found - 0 modified | TOTAL: 0 pass 1 (yz-): 0 found - 0 modified | TOTAL: 0 pass 1 (xz+): 0 found - 0 modified | TOTAL: 0 pass 1 (xz-): 0 found - 0 modified | TOTAL: 0 Iteration Number : 3 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 Iteration Number : 3 pass 1 (++): 0 found - 0 modified | TOTAL: 0 pass 1 (+-): 0 found - 0 modified | TOTAL: 0 pass 1 (--): 0 found - 0 modified | TOTAL: 0 pass 1 (-+): 0 found - 0 modified | TOTAL: 0 Total Number of Modified Voxels = 39 (out of 297074: 0.013128) Ambiguous edge configurations... mri_pretess done @#@FSTIME 2021:11:09:19:37:49 mri_pretess N 4 e 1.45 S 0.00 U 1.99 P 137% M 40312 F 0 R 8850 W 0 c 8 w 7 I 0 O 304 L 1.00 1.00 1.00 @#@FSLOADPOST 2021:11:09:19:37:50 mri_pretess N 4 1.00 1.00 1.00 mri_tessellate ../mri/filled-pretess127.mgz 127 ../surf/rh.orig.nofix dev dev slice 40: 1758 vertices, 1880 faces slice 50: 9248 vertices, 9584 faces slice 60: 19306 vertices, 19696 faces slice 70: 31794 vertices, 32244 faces slice 80: 43434 vertices, 43910 faces slice 90: 55817 vertices, 56294 faces slice 100: 69188 vertices, 69792 faces slice 110: 82951 vertices, 83592 faces slice 120: 97506 vertices, 98192 faces slice 130: 111174 vertices, 111855 faces slice 140: 122116 vertices, 122680 faces slice 150: 131236 vertices, 131796 faces slice 160: 140128 vertices, 140774 faces slice 170: 149173 vertices, 149833 faces slice 180: 156384 vertices, 156996 faces slice 190: 163096 vertices, 163735 faces slice 200: 167956 vertices, 168467 faces slice 210: 168520 vertices, 168930 faces slice 220: 168520 vertices, 168930 faces slice 230: 168520 vertices, 168930 faces slice 240: 168520 vertices, 168930 faces slice 250: 168520 vertices, 168930 faces using the conformed surface RAS to save vertex points... writing ../surf/rh.orig.nofix using vox2ras matrix: -1.00000 0.00000 0.00000 128.00000; 0.00000 0.00000 1.00000 -128.00000; 0.00000 -1.00000 0.00000 128.00000; 0.00000 0.00000 0.00000 1.00000; @#@FSTIME 2021:11:09:19:37:50 mri_tessellate N 3 e 1.08 S 0.01 U 1.33 P 124% M 40404 F 0 R 9118 W 0 c 5 w 4 I 0 O 7912 L 1.00 1.00 1.00 @#@FSLOADPOST 2021:11:09:19:37:52 mri_tessellate N 3 1.00 1.00 1.00 rm -f ../mri/filled-pretess127.mgz mris_extract_main_component ../surf/rh.orig.nofix ../surf/rh.orig.nofix counting number of connected components... 168520 voxel in cpt #1: X=-410 [v=168520,e=506790,f=337860] located at (23.482916, -16.115797, 8.208622) For the whole surface: X=-410 [v=168520,e=506790,f=337860] One single component has been found nothing to do done @#@FSTIME 2021:11:09:19:37:52 mris_extract_main_component N 2 e 0.86 S 0.13 U 1.05 P 137% M 334292 F 0 R 88902 W 0 c 12 w 13 I 0 O 11872 L 1.00 1.00 1.00 @#@FSLOADPOST 2021:11:09:19:37:52 mris_extract_main_component N 2 1.00 1.00 1.00 #-------------------------------------------- #@# Smooth1 lh Tue Nov 9 19:37:52 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/scripts mris_smooth -nw -seed 1234 ../surf/lh.orig.nofix ../surf/lh.smoothwm.nofix #-------------------------------------------- #@# Smooth1 rh Tue Nov 9 19:37:52 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/scripts mris_smooth -nw -seed 1234 ../surf/rh.orig.nofix ../surf/rh.smoothwm.nofix Waiting for PID 6201 of (6201 6204) to complete... Waiting for PID 6204 of (6201 6204) to complete... mris_smooth -nw -seed 1234 ../surf/lh.orig.nofix ../surf/lh.smoothwm.nofix setting seed for random number generator to 1234 smoothing surface tessellation for 10 iterations... smoothing complete - recomputing first and second fundamental forms... mris_smooth -nw -seed 1234 ../surf/rh.orig.nofix ../surf/rh.smoothwm.nofix setting seed for random number generator to 1234 smoothing surface tessellation for 10 iterations... smoothing complete - recomputing first and second fundamental forms... PIDs (6201 6204) completed and logs appended. #-------------------------------------------- #@# Inflation1 lh Tue Nov 9 19:37:55 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/scripts mris_inflate -no-save-sulc ../surf/lh.smoothwm.nofix ../surf/lh.inflated.nofix #-------------------------------------------- #@# Inflation1 rh Tue Nov 9 19:37:55 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/scripts mris_inflate -no-save-sulc ../surf/rh.smoothwm.nofix ../surf/rh.inflated.nofix Waiting for PID 6249 of (6249 6252) to complete... Waiting for PID 6252 of (6249 6252) to complete... mris_inflate -no-save-sulc ../surf/lh.smoothwm.nofix ../surf/lh.inflated.nofix Not saving sulc Reading ../surf/lh.smoothwm.nofix avg radius = 49.4 mm, total surface area = 83583 mm^2 step 000: RMS=0.179 (target=0.015) step 005: RMS=0.142 (target=0.015) step 010: RMS=0.119 (target=0.015) step 015: RMS=0.108 (target=0.015) step 020: RMS=0.100 (target=0.015) step 025: RMS=0.092 (target=0.015) step 030: RMS=0.088 (target=0.015) step 035: RMS=0.085 (target=0.015) step 040: RMS=0.083 (target=0.015) step 045: RMS=0.081 (target=0.015) step 050: RMS=0.080 (target=0.015) step 055: RMS=0.080 (target=0.015) step 060: RMS=0.081 (target=0.015) writing inflated surface to ../surf/lh.inflated.nofix inflation took 0.2 minutes inflation complete. Not saving sulc mris_inflate utimesec 36.954067 mris_inflate stimesec 0.822806 mris_inflate ru_maxrss 259272 mris_inflate ru_ixrss 0 mris_inflate ru_idrss 0 mris_inflate ru_isrss 0 mris_inflate ru_minflt 694768 mris_inflate ru_majflt 17 mris_inflate ru_nswap 0 mris_inflate ru_inblock 2184 mris_inflate ru_oublock 11504 mris_inflate ru_msgsnd 0 mris_inflate ru_msgrcv 0 mris_inflate ru_nsignals 0 mris_inflate ru_nvcsw 3878 mris_inflate ru_nivcsw 123 mris_inflate -no-save-sulc ../surf/rh.smoothwm.nofix ../surf/rh.inflated.nofix Not saving sulc Reading ../surf/rh.smoothwm.nofix avg radius = 48.7 mm, total surface area = 85575 mm^2 step 000: RMS=0.182 (target=0.015) step 005: RMS=0.145 (target=0.015) step 010: RMS=0.121 (target=0.015) step 015: RMS=0.111 (target=0.015) step 020: RMS=0.103 (target=0.015) step 025: RMS=0.097 (target=0.015) step 030: RMS=0.093 (target=0.015) step 035: RMS=0.088 (target=0.015) step 040: RMS=0.086 (target=0.015) step 045: RMS=0.085 (target=0.015) step 050: RMS=0.084 (target=0.015) step 055: RMS=0.083 (target=0.015) step 060: RMS=0.083 (target=0.015) writing inflated surface to ../surf/rh.inflated.nofix inflation took 0.2 minutes inflation complete. Not saving sulc mris_inflate utimesec 36.663418 mris_inflate stimesec 0.818397 mris_inflate ru_maxrss 267220 mris_inflate ru_ixrss 0 mris_inflate ru_idrss 0 mris_inflate ru_isrss 0 mris_inflate ru_minflt 706747 mris_inflate ru_majflt 13 mris_inflate ru_nswap 0 mris_inflate ru_inblock 1552 mris_inflate ru_oublock 11872 mris_inflate ru_msgsnd 0 mris_inflate ru_msgrcv 0 mris_inflate ru_nsignals 0 mris_inflate ru_nvcsw 4352 mris_inflate ru_nivcsw 131 PIDs (6249 6252) completed and logs appended. #-------------------------------------------- #@# QSphere lh Tue Nov 9 19:38:09 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/scripts mris_sphere -q -p 6 -a 128 -seed 1234 ../surf/lh.inflated.nofix ../surf/lh.qsphere.nofix #-------------------------------------------- #@# QSphere rh Tue Nov 9 19:38:09 EST 2021 /home/basuia/Documents/mmvt_root/subjects/UC07/scripts mris_sphere -q -p 6 -a 128 -seed 1234 ../surf/rh.inflated.nofix ../surf/rh.qsphere.nofix Waiting for PID 6297 of (6297 6300) to complete... Waiting for PID 6300 of (6297 6300) to complete... mris_sphere -q -p 6 -a 128 -seed 1234 ../surf/lh.inflated.nofix ../surf/lh.qsphere.nofix doing quick spherical unfolding. limitting unfolding to 6 passes using n_averages = 128 setting seed for random number genererator to 1234 version: dev available threads: 4 scaling brain by 0.285... inflating... projecting onto sphere... surface projected - minimizing metric distortion... vertex spacing 0.89 +- 0.60 (0.00-->11.11) (max @ vno 84980 --> 84981) face area 0.02 +- 0.03 (-0.24-->0.64) Entering MRISinflateToSphere() inflating to sphere (rms error < 2.00) 000: dt: 0.0000, rms radial error=177.311, avgs=0 005/300: dt: 0.9000, rms radial error=177.049, avgs=0 010/300: dt: 0.9000, rms radial error=176.488, avgs=0 015/300: dt: 0.9000, rms radial error=175.753, avgs=0 020/300: dt: 0.9000, rms radial error=174.917, avgs=0 025/300: dt: 0.9000, rms radial error=174.023, avgs=0 030/300: dt: 0.9000, rms radial error=173.097, avgs=0 035/300: dt: 0.9000, rms radial error=172.154, avgs=0 040/300: dt: 0.9000, rms radial error=171.203, avgs=0 045/300: dt: 0.9000, rms radial error=170.249, avgs=0 050/300: dt: 0.9000, rms radial error=169.296, avgs=0 055/300: dt: 0.9000, rms radial error=168.346, avgs=0 060/300: dt: 0.9000, rms radial error=167.399, avgs=0 065/300: dt: 0.9000, rms radial error=166.456, avgs=0 070/300: dt: 0.9000, rms radial error=165.517, avgs=0 075/300: dt: 0.9000, rms radial error=164.583, avgs=0 080/300: dt: 0.9000, rms radial error=163.657, avgs=0 085/300: dt: 0.9000, rms radial error=162.737, avgs=0 090/300: dt: 0.9000, rms radial error=161.823, avgs=0 095/300: dt: 0.9000, rms radial error=160.914, avgs=0 100/300: dt: 0.9000, rms radial error=160.010, avgs=0 105/300: dt: 0.9000, rms radial error=159.111, avgs=0 110/300: dt: 0.9000, rms radial error=158.216, avgs=0 115/300: dt: 0.9000, rms radial error=157.327, avgs=0 120/300: dt: 0.9000, rms radial error=156.442, avgs=0 125/300: dt: 0.9000, rms radial error=155.562, avgs=0 130/300: dt: 0.9000, rms radial error=154.687, avgs=0 135/300: dt: 0.9000, rms radial error=153.817, avgs=0 140/300: dt: 0.9000, rms radial error=152.951, avgs=0 145/300: dt: 0.9000, rms radial error=152.090, avgs=0 150/300: dt: 0.9000, rms radial error=151.234, avgs=0 155/300: dt: 0.9000, rms radial error=150.382, avgs=0 160/300: dt: 0.9000, rms radial error=149.536, avgs=0 165/300: dt: 0.9000, rms radial error=148.694, avgs=0 170/300: dt: 0.9000, rms radial error=147.856, avgs=0 175/300: dt: 0.9000, rms radial error=147.023, avgs=0 180/300: dt: 0.9000, rms radial error=146.195, avgs=0 185/300: dt: 0.9000, rms radial error=145.371, avgs=0 190/300: dt: 0.9000, rms radial error=144.552, avgs=0 195/300: dt: 0.9000, rms radial error=143.737, avgs=0 200/300: dt: 0.9000, rms radial error=142.927, avgs=0 205/300: dt: 0.9000, rms radial error=142.122, avgs=0 210/300: dt: 0.9000, rms radial error=141.320, avgs=0 215/300: dt: 0.9000, rms radial error=140.524, avgs=0 220/300: dt: 0.9000, rms radial error=139.732, avgs=0 225/300: dt: 0.9000, rms radial error=138.944, avgs=0 230/300: dt: 0.9000, rms radial error=138.161, avgs=0 235/300: dt: 0.9000, rms radial error=137.383, avgs=0 240/300: dt: 0.9000, rms radial error=136.608, avgs=0 245/300: dt: 0.9000, rms radial error=135.839, avgs=0 250/300: dt: 0.9000, rms radial error=135.073, avgs=0 255/300: dt: 0.9000, rms radial error=134.311, avgs=0 260/300: dt: 0.9000, rms radial error=133.554, avgs=0 265/300: dt: 0.9000, rms radial error=132.801, avgs=0 270/300: dt: 0.9000, rms radial error=132.052, avgs=0 275/300: dt: 0.9000, rms radial error=131.308, avgs=0 280/300: dt: 0.9000, rms radial error=130.567, avgs=0 285/300: dt: 0.9000, rms radial error=129.831, avgs=0 290/300: dt: 0.9000, rms radial error=129.099, avgs=0 295/300: dt: 0.9000, rms radial error=128.371, avgs=0 300/300: dt: 0.9000, rms radial error=127.647, avgs=0 spherical inflation complete. epoch 1 (K=10.0), pass 1, starting sse = 19814.56 taking momentum steps... taking momentum steps... taking momentum steps... taking momentum steps... pass 1 complete, delta sse/iter = 0.00/13 = 0.00032 epoch 2 (K=40.0), pass 1, starting sse = 3597.88 taking momentum steps... taking momentum steps... taking momentum steps... taking momentum steps... pass 1 complete, delta sse/iter = 0.00/13 = 0.00016 epoch 3 (K=160.0), pass 1, starting sse = 476.85 taking momentum steps... taking momentum steps... taking momentum steps... taking momentum steps... pass 1 complete, delta sse/iter = 0.02/13 = 0.00188 epoch 4 (K=640.0), pass 1, starting sse = 65.98 taking momentum steps... taking momentum steps... taking momentum steps... taking momentum steps... pass 1 complete, delta sse/iter = 0.08/18 = 0.00449 final distance error %100000.00 writing spherical brain to ../surf/lh.qsphere.nofix spherical transformation took 0.0256 hours FSRUNTIME@ mris_sphere 0.0256 hours 4 threads #VMPC# mris_sphere VmPeak 838380 mris_sphere done mris_sphere -q -p 6 -a 128 -seed 1234 ../surf/rh.inflated.nofix ../surf/rh.qsphere.nofix doing quick spherical unfolding. limitting unfolding to 6 passes using n_averages = 128 setting seed for random number genererator to 1234 version: dev available threads: 4 scaling brain by 0.293... inflating... projecting onto sphere... surface projected - minimizing metric distortion... vertex spacing 0.92 +- 0.75 (0.00-->51.63) (max @ vno 95362 --> 96761) face area 0.02 +- 0.05 (-4.91-->2.99) Entering MRISinflateToSphere() inflating to sphere (rms error < 2.00) 000: dt: 0.0000, rms radial error=177.039, avgs=0 005/300: dt: 0.9000, rms radial error=176.778, avgs=0 010/300: dt: 0.9000, rms radial error=176.220, avgs=0 015/300: dt: 0.9000, rms radial error=175.485, avgs=0 020/300: dt: 0.9000, rms radial error=174.649, avgs=0 025/300: dt: 0.9000, rms radial error=173.756, avgs=0 030/300: dt: 0.9000, rms radial error=172.832, avgs=0 035/300: dt: 0.9000, rms radial error=171.892, avgs=0 040/300: dt: 0.9000, rms radial error=170.945, avgs=0 045/300: dt: 0.9000, rms radial error=169.996, avgs=0 050/300: dt: 0.9000, rms radial error=169.048, avgs=0 055/300: dt: 0.9000, rms radial error=168.104, avgs=0 060/300: dt: 0.9000, rms radial error=167.164, avgs=0 065/300: dt: 0.9000, rms radial error=166.230, avgs=0 070/300: dt: 0.9000, rms radial error=165.303, avgs=0 075/300: dt: 0.9000, rms radial error=164.381, avgs=0 080/300: dt: 0.9000, rms radial error=163.464, avgs=0 085/300: dt: 0.9000, rms radial error=162.553, avgs=0 090/300: dt: 0.9000, rms radial error=161.647, avgs=0 095/300: dt: 0.9000, rms radial error=160.746, avgs=0 100/300: dt: 0.9000, rms radial error=159.851, avgs=0 105/300: dt: 0.9000, rms radial error=158.961, avgs=0 110/300: dt: 0.9000, rms radial error=158.077, avgs=0 115/300: dt: 0.9000, rms radial error=157.197, avgs=0 120/300: dt: 0.9000, rms radial error=156.323, avgs=0 125/300: dt: 0.9000, rms radial error=155.453, avgs=0 130/300: dt: 0.9000, rms radial error=154.588, avgs=0 135/300: dt: 0.9000, rms radial error=153.727, avgs=0 140/300: dt: 0.9000, rms radial error=152.872, avgs=0 145/300: dt: 0.9000, rms radial error=152.021, avgs=0 150/300: dt: 0.9000, rms radial error=151.174, avgs=0 155/300: dt: 0.9000, rms radial error=150.332, avgs=0 160/300: dt: 0.9000, rms radial error=149.495, avgs=0 165/300: dt: 0.9000, rms radial error=148.662, avgs=0 170/300: dt: 0.9000, rms radial error=147.835, avgs=0 175/300: dt: 0.9000, rms radial error=147.011, avgs=0 180/300: dt: 0.9000, rms radial error=146.193, avgs=0 185/300: dt: 0.9000, rms radial error=145.379, avgs=0 190/300: dt: 0.9000, rms radial error=144.570, avgs=0 195/300: dt: 0.9000, rms radial error=143.765, avgs=0 200/300: dt: 0.9000, rms radial error=142.965, avgs=0 205/300: dt: 0.9000, rms radial error=142.169, avgs=0 210/300: dt: 0.9000, rms radial error=141.378, avgs=0 215/300: dt: 0.9000, rms radial error=140.590, avgs=0 220/300: dt: 0.9000, rms radial error=139.807, avgs=0 225/300: dt: 0.9000, rms radial error=139.029, avgs=0 230/300: dt: 0.9000, rms radial error=138.254, avgs=0 235/300: dt: 0.9000, rms radial error=137.484, avgs=0 240/300: dt: 0.9000, rms radial error=136.718, avgs=0 245/300: dt: 0.9000, rms radial error=135.956, avgs=0 250/300: dt: 0.9000, rms radial error=135.199, avgs=0 255/300: dt: 0.9000, rms radial error=134.446, avgs=0 260/300: dt: 0.9000, rms radial error=133.697, avgs=0 265/300: dt: 0.9000, rms radial error=132.952, avgs=0 270/300: dt: 0.9000, rms radial error=132.211, avgs=0 275/300: dt: 0.9000, rms radial error=131.475, avgs=0 280/300: dt: 0.9000, rms radial error=130.742, avgs=0 285/300: dt: 0.9000, rms radial error=130.014, avgs=0 290/300: dt: 0.9000, rms radial error=129.289, avgs=0 295/300: dt: 0.9000, rms radial error=128.569, avgs=0 300/300: dt: 0.9000, rms radial error=127.852, avgs=0 spherical inflation complete. epoch 1 (K=10.0), pass 1, starting sse = 20559.44 taking momentum steps... taking momentum steps... taking momentum steps... taking momentum steps... pass 1 complete, delta sse/iter = 0.01/13 = 0.00044 epoch 2 (K=40.0), pass 1, starting sse = 3898.32 taking momentum steps... taking momentum steps... taking momentum steps... taking momentum steps... pass 1 complete, delta sse/iter = 0.01/13 = 0.00061 epoch 3 (K=160.0), pass 1, starting sse = 586.19 taking momentum steps... taking momentum steps... taking momentum steps... taking momentum steps... pass 1 complete, delta sse/iter = 0.05/13 = 0.00365 epoch 4 (K=640.0), pass 1, starting sse = 115.65 taking momentum steps... taking momentum steps... taking momentum steps... taking momentum steps... pass 1 complete, delta sse/iter = 0.16/19 = 0.00841 final distance error %100000.00 writing spherical brain to ../surf/rh.qsphere.nofix spherical transformation took 0.0269 hours FSRUNTIME@ mris_sphere 0.0269 hours 4 threads #VMPC# mris_sphere VmPeak 842604 mris_sphere done PIDs (6297 6300) completed and logs appended. #@# Fix Topology lh Tue Nov 9 19:39:46 EST 2021 mris_fix_topology -mgz -sphere qsphere.nofix -inflated inflated.nofix -orig orig.nofix -out orig.premesh -ga -seed 1234 UC07 lh #@# Fix Topology rh Tue Nov 9 19:39:46 EST 2021 mris_fix_topology -mgz -sphere qsphere.nofix -inflated inflated.nofix -orig orig.nofix -out orig.premesh -ga -seed 1234 UC07 rh Waiting for PID 6337 of (6337 6340) to complete... Waiting for PID 6340 of (6337 6340) to complete... /home/basuia/Documents/mmvt_root/freesurfer/bin/reconbatchjobs: line 77: 6340 Segmentation fault (core dumped) exec $JOB >> $LOG 2>&1 mris_fix_topology -mgz -sphere qsphere.nofix -inflated inflated.nofix -orig orig.nofix -out orig.premesh -ga -seed 1234 UC07 lh reading spherical homeomorphism from 'qsphere.nofix' reading inflated coordinates from 'inflated.nofix' reading original coordinates from 'orig.nofix' using genetic algorithm with optimized parameters setting seed for random number genererator to 1234 ************************************************************* Topology Correction Parameters retessellation mode: genetic search number of patches/generation : 10 number of generations : 10 surface mri loglikelihood coefficient : 1.0 volume mri loglikelihood coefficient : 10.0 normal dot loglikelihood coefficient : 1.0 quadratic curvature loglikelihood coefficient : 1.0 volume resolution : 2 eliminate vertices during search : 1 initial patch selection : 1 select all defect vertices : 0 ordering dependant retessellation: 0 use precomputed edge table : 0 smooth retessellated patch : 2 match retessellated patch : 1 verbose mode : 0 ************************************************************* INFO: assuming .mgz format writing corrected surface to 'orig.premesh' dev dev before topology correction, eno=-402 (nv=163290, nf=327384, ne=491076, g=202) using quasi-homeomorphic spherical map to tessellate cortical surface... Correction of the Topology Finding true center and radius of Spherical Surface...done Surface centered at (0,0,0) with radius 100.0 in 10 iterations marking ambiguous vertices... 32616 ambiguous faces found in tessellation segmenting defects... 130 defects found, arbitrating ambiguous regions... analyzing neighboring defects... -merging segment 58 into 47 -merging segment 67 into 47 -merging segment 80 into 47 -merging segment 72 into 61 -merging segment 68 into 63 -merging segment 78 into 73 -merging segment 93 into 94 -merging segment 101 into 95 -merging segment 117 into 95 -merging segment 122 into 95 -merging segment 125 into 95 119 defects to be corrected 0 vertices coincident reading input surface /home/basuia/Documents/mmvt_root/subjects/UC07/surf/lh.qsphere.nofix... reading brain volume from brain... reading wm segmentation from wm... Reading original properties of orig.nofix Reading vertex positions of inflated.nofix Computing Initial Surface Statistics -face loglikelihood: -9.2292 (-4.6146) -vertex loglikelihood: -6.5184 (-3.2592) -normal dot loglikelihood: -3.5383 (-3.5383) -quad curv loglikelihood: -6.3127 (-3.1563) Total Loglikelihood : -25.5986 CORRECTING DEFECT 0 (vertices=158, convex hull=119, v0=948) After retessellation of defect 0 (v0=948), euler #=-114 (144682,429162,284366) : difference with theory (-116) = -2 CORRECTING DEFECT 1 (vertices=7, convex hull=26, v0=1224) After retessellation of defect 1 (v0=1224), euler #=-113 (144682,429169,284374) : difference with theory (-115) = -2 CORRECTING DEFECT 2 (vertices=37, convex hull=68, v0=3091) After retessellation of defect 2 (v0=3091), euler #=-112 (144700,429249,284437) : difference with theory (-114) = -2 CORRECTING DEFECT 3 (vertices=311, convex hull=179, v0=3784) After retessellation of defect 3 (v0=3784), euler #=-111 (144752,429487,284624) : difference with theory (-113) = -2 CORRECTING DEFECT 4 (vertices=11, convex hull=47, v0=12818) After retessellation of defect 4 (v0=12818), euler #=-110 (144756,429512,284646) : difference with theory (-112) = -2 CORRECTING DEFECT 5 (vertices=30, convex hull=55, v0=14208) After retessellation of defect 5 (v0=14208), euler #=-109 (144768,429575,284698) : difference with theory (-111) = -2 CORRECTING DEFECT 6 (vertices=24, convex hull=55, v0=14418) After retessellation of defect 6 (v0=14418), euler #=-108 (144781,429634,284745) : difference with theory (-110) = -2 CORRECTING DEFECT 7 (vertices=57, convex hull=69, v0=17243) After retessellation of defect 7 (v0=17243), euler #=-107 (144794,429698,284797) : difference with theory (-109) = -2 CORRECTING DEFECT 8 (vertices=108, convex hull=40, v0=17847) After retessellation of defect 8 (v0=17847), euler #=-106 (144802,429733,284825) : difference with theory (-108) = -2 CORRECTING DEFECT 9 (vertices=200, convex hull=180, v0=20084) After retessellation of defect 9 (v0=20084), euler #=-105 (144886,430069,285078) : difference with theory (-107) = -2 CORRECTING DEFECT 10 (vertices=28, convex hull=54, v0=20600) After retessellation of defect 10 (v0=20600), euler #=-104 (144897,430120,285119) : difference with theory (-106) = -2 CORRECTING DEFECT 11 (vertices=5, convex hull=19, v0=24258) After retessellation of defect 11 (v0=24258), euler #=-103 (144898,430128,285127) : difference with theory (-105) = -2 CORRECTING DEFECT 12 (vertices=44, convex hull=65, v0=24551) After retessellation of defect 12 (v0=24551), euler #=-102 (144920,430218,285196) : difference with theory (-104) = -2 CORRECTING DEFECT 13 (vertices=43, convex hull=61, v0=24885) After retessellation of defect 13 (v0=24885), euler #=-101 (144930,430269,285238) : difference with theory (-103) = -2 CORRECTING DEFECT 14 (vertices=35, convex hull=68, v0=28464) After retessellation of defect 14 (v0=28464), euler #=-100 (144941,430330,285289) : difference with theory (-102) = -2 CORRECTING DEFECT 15 (vertices=25, convex hull=76, v0=29840) After retessellation of defect 15 (v0=29840), euler #=-99 (144952,430392,285341) : difference with theory (-101) = -2 CORRECTING DEFECT 16 (vertices=5, convex hull=17, v0=33951) After retessellation of defect 16 (v0=33951), euler #=-98 (144952,430397,285347) : difference with theory (-100) = -2 CORRECTING DEFECT 17 (vertices=22, convex hull=51, v0=34325) After retessellation of defect 17 (v0=34325), euler #=-97 (144962,430448,285389) : difference with theory (-99) = -2 CORRECTING DEFECT 18 (vertices=5, convex hull=18, v0=34759) After retessellation of defect 18 (v0=34759), euler #=-96 (144962,430453,285395) : difference with theory (-98) = -2 CORRECTING DEFECT 19 (vertices=32, convex hull=29, v0=35385) After retessellation of defect 19 (v0=35385), euler #=-95 (144966,430475,285414) : difference with theory (-97) = -2 CORRECTING DEFECT 20 (vertices=7, convex hull=26, v0=36646) After retessellation of defect 20 (v0=36646), euler #=-94 (144967,430486,285425) : difference with theory (-96) = -2 CORRECTING DEFECT 21 (vertices=89, convex hull=144, v0=38027) After retessellation of defect 21 (v0=38027), euler #=-93 (145017,430699,285589) : difference with theory (-95) = -2 CORRECTING DEFECT 22 (vertices=6, convex hull=20, v0=40332) After retessellation of defect 22 (v0=40332), euler #=-92 (145018,430707,285597) : difference with theory (-94) = -2 CORRECTING DEFECT 23 (vertices=47, convex hull=48, v0=44873) After retessellation of defect 23 (v0=44873), euler #=-91 (145038,430787,285658) : difference with theory (-93) = -2 CORRECTING DEFECT 24 (vertices=55, convex hull=35, v0=45007) After retessellation of defect 24 (v0=45007), euler #=-90 (145046,430821,285685) : difference with theory (-92) = -2 CORRECTING DEFECT 25 (vertices=37, convex hull=72, v0=46180) After retessellation of defect 25 (v0=46180), euler #=-89 (145064,430907,285754) : difference with theory (-91) = -2 CORRECTING DEFECT 26 (vertices=407, convex hull=270, v0=50939) After retessellation of defect 26 (v0=50939), euler #=-88 (145129,431235,286018) : difference with theory (-90) = -2 CORRECTING DEFECT 27 (vertices=23, convex hull=21, v0=51445) After retessellation of defect 27 (v0=51445), euler #=-87 (145131,431247,286029) : difference with theory (-89) = -2 CORRECTING DEFECT 28 (vertices=24, convex hull=46, v0=53208) After retessellation of defect 28 (v0=53208), euler #=-86 (145141,431293,286066) : difference with theory (-88) = -2 CORRECTING DEFECT 29 (vertices=9, convex hull=18, v0=54779) After retessellation of defect 29 (v0=54779), euler #=-85 (145145,431309,286079) : difference with theory (-87) = -2 CORRECTING DEFECT 30 (vertices=326, convex hull=261, v0=54829) After retessellation of defect 30 (v0=54829), euler #=-84 (145204,431633,286345) : difference with theory (-86) = -2 CORRECTING DEFECT 31 (vertices=87, convex hull=125, v0=56264) After retessellation of defect 31 (v0=56264), euler #=-83 (145243,431802,286476) : difference with theory (-85) = -2 CORRECTING DEFECT 32 (vertices=28, convex hull=76, v0=56481) After retessellation of defect 32 (v0=56481), euler #=-82 (145258,431875,286535) : difference with theory (-84) = -2 CORRECTING DEFECT 33 (vertices=36, convex hull=68, v0=57966) After retessellation of defect 33 (v0=57966), euler #=-81 (145274,431949,286594) : difference with theory (-83) = -2 CORRECTING DEFECT 34 (vertices=252, convex hull=59, v0=61662) After retessellation of defect 34 (v0=61662), euler #=-80 (145286,432009,286643) : difference with theory (-82) = -2 CORRECTING DEFECT 35 (vertices=12, convex hull=23, v0=61735) After retessellation of defect 35 (v0=61735), euler #=-79 (145287,432018,286652) : difference with theory (-81) = -2 CORRECTING DEFECT 36 (vertices=134, convex hull=62, v0=62539) After retessellation of defect 36 (v0=62539), euler #=-78 (145312,432116,286726) : difference with theory (-80) = -2 CORRECTING DEFECT 37 (vertices=63, convex hull=70, v0=64572) After retessellation of defect 37 (v0=64572), euler #=-77 (145323,432182,286782) : difference with theory (-79) = -2 CORRECTING DEFECT 38 (vertices=7, convex hull=29, v0=67055) After retessellation of defect 38 (v0=67055), euler #=-76 (145327,432202,286799) : difference with theory (-78) = -2 CORRECTING DEFECT 39 (vertices=15, convex hull=40, v0=68540) After retessellation of defect 39 (v0=68540), euler #=-75 (145332,432230,286823) : difference with theory (-77) = -2 CORRECTING DEFECT 40 (vertices=57, convex hull=71, v0=71068) After retessellation of defect 40 (v0=71068), euler #=-74 (145350,432316,286892) : difference with theory (-76) = -2 CORRECTING DEFECT 41 (vertices=42, convex hull=81, v0=71407) After retessellation of defect 41 (v0=71407), euler #=-73 (145373,432416,286970) : difference with theory (-75) = -2 CORRECTING DEFECT 42 (vertices=69, convex hull=123, v0=72855) After retessellation of defect 42 (v0=72855), euler #=-72 (145419,432610,287119) : difference with theory (-74) = -2 CORRECTING DEFECT 43 (vertices=38, convex hull=79, v0=73385) After retessellation of defect 43 (v0=73385), euler #=-71 (145441,432707,287195) : difference with theory (-73) = -2 CORRECTING DEFECT 44 (vertices=127, convex hull=108, v0=73954) After retessellation of defect 44 (v0=73954), euler #=-70 (145476,432856,287310) : difference with theory (-72) = -2 CORRECTING DEFECT 45 (vertices=29, convex hull=49, v0=74919) After retessellation of defect 45 (v0=74919), euler #=-69 (145488,432909,287352) : difference with theory (-71) = -2 CORRECTING DEFECT 46 (vertices=238, convex hull=183, v0=74921) After retessellation of defect 46 (v0=74921), euler #=-68 (145565,433235,287602) : difference with theory (-70) = -2 CORRECTING DEFECT 47 (vertices=6231, convex hull=1339, v0=76502) An extra large defect has been detected... This often happens because cerebellum or dura has not been removed from wm.mgz. This may cause recon-all to run very slowly or crash. if so, see https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/TopologicalDefect_freeview After retessellation of defect 47 (v0=76502), euler #=-71 (146133,435701,289497) : difference with theory (-69) = 2 CORRECTING DEFECT 48 (vertices=24, convex hull=32, v0=78372) After retessellation of defect 48 (v0=78372), euler #=-70 (146136,435722,289516) : difference with theory (-68) = 2 CORRECTING DEFECT 49 (vertices=35, convex hull=45, v0=79403) After retessellation of defect 49 (v0=79403), euler #=-69 (146146,435769,289554) : difference with theory (-67) = 2 CORRECTING DEFECT 50 (vertices=38, convex hull=60, v0=81024) After retessellation of defect 50 (v0=81024), euler #=-68 (146169,435861,289624) : difference with theory (-66) = 2 CORRECTING DEFECT 51 (vertices=304, convex hull=217, v0=81534) After retessellation of defect 51 (v0=81534), euler #=-68 (146267,436260,289925) : difference with theory (-65) = 3 CORRECTING DEFECT 52 (vertices=21, convex hull=41, v0=81896) After retessellation of defect 52 (v0=81896), euler #=-67 (146279,436310,289964) : difference with theory (-64) = 3 CORRECTING DEFECT 53 (vertices=27, convex hull=29, v0=82308) After retessellation of defect 53 (v0=82308), euler #=-66 (146287,436342,289989) : difference with theory (-63) = 3 CORRECTING DEFECT 54 (vertices=19, convex hull=33, v0=83044) After retessellation of defect 54 (v0=83044), euler #=-65 (146290,436358,290003) : difference with theory (-62) = 3 CORRECTING DEFECT 55 (vertices=18, convex hull=37, v0=83370) After retessellation of defect 55 (v0=83370), euler #=-64 (146296,436390,290030) : difference with theory (-61) = 3 CORRECTING DEFECT 56 (vertices=7, convex hull=23, v0=83405) After retessellation of defect 56 (v0=83405), euler #=-63 (146298,436404,290043) : difference with theory (-60) = 3 CORRECTING DEFECT 57 (vertices=71, convex hull=81, v0=84044) After retessellation of defect 57 (v0=84044), euler #=-62 (146321,436506,290123) : difference with theory (-59) = 3 CORRECTING DEFECT 58 (vertices=7, convex hull=16, v0=86100) After retessellation of defect 58 (v0=86100), euler #=-61 (146323,436516,290132) : difference with theory (-58) = 3 CORRECTING DEFECT 59 (vertices=458, convex hull=238, v0=86794) After retessellation of defect 59 (v0=86794), euler #=-62 (146447,437024,290515) : difference with theory (-57) = 5 CORRECTING DEFECT 60 (vertices=1341, convex hull=412, v0=87292) After retessellation of defect 60 (v0=87292), euler #=-60 (146562,437577,290955) : difference with theory (-56) = 4 CORRECTING DEFECT 61 (vertices=75, convex hull=88, v0=88036) After retessellation of defect 61 (v0=88036), euler #=-59 (146580,437669,291030) : difference with theory (-55) = 4 CORRECTING DEFECT 62 (vertices=78, convex hull=94, v0=91066) After retessellation of defect 62 (v0=91066), euler #=-57 (146596,437762,291109) : difference with theory (-54) = 3 CORRECTING DEFECT 63 (vertices=6, convex hull=22, v0=93277) After retessellation of defect 63 (v0=93277), euler #=-56 (146597,437772,291119) : difference with theory (-53) = 3 CORRECTING DEFECT 64 (vertices=15, convex hull=25, v0=94072) After retessellation of defect 64 (v0=94072), euler #=-55 (146598,437781,291128) : difference with theory (-52) = 3 CORRECTING DEFECT 65 (vertices=121, convex hull=126, v0=94578) After retessellation of defect 65 (v0=94578), euler #=-54 (146666,438043,291323) : difference with theory (-51) = 3 CORRECTING DEFECT 66 (vertices=417, convex hull=174, v0=97743) After retessellation of defect 66 (v0=97743), euler #=-53 (146697,438217,291467) : difference with theory (-50) = 3 CORRECTING DEFECT 67 (vertices=30, convex hull=60, v0=98208) After retessellation of defect 67 (v0=98208), euler #=-52 (146706,438268,291510) : difference with theory (-49) = 3 CORRECTING DEFECT 68 (vertices=14, convex hull=29, v0=99647) After retessellation of defect 68 (v0=99647), euler #=-51 (146713,438299,291535) : difference with theory (-48) = 3 CORRECTING DEFECT 69 (vertices=319, convex hull=273, v0=103822) After retessellation of defect 69 (v0=103822), euler #=-51 (146860,438914,292003) : difference with theory (-47) = 4 CORRECTING DEFECT 70 (vertices=58, convex hull=88, v0=104413) After retessellation of defect 70 (v0=104413), euler #=-50 (146899,439067,292118) : difference with theory (-46) = 4 CORRECTING DEFECT 71 (vertices=7, convex hull=20, v0=105700) After retessellation of defect 71 (v0=105700), euler #=-49 (146901,439077,292127) : difference with theory (-45) = 4 CORRECTING DEFECT 72 (vertices=32, convex hull=60, v0=106040) After retessellation of defect 72 (v0=106040), euler #=-48 (146917,439146,292181) : difference with theory (-44) = 4 CORRECTING DEFECT 73 (vertices=115, convex hull=157, v0=106061) After retessellation of defect 73 (v0=106061), euler #=-47 (146981,439418,292390) : difference with theory (-43) = 4 CORRECTING DEFECT 74 (vertices=16, convex hull=49, v0=106387) After retessellation of defect 74 (v0=106387), euler #=-46 (146992,439470,292432) : difference with theory (-42) = 4 CORRECTING DEFECT 75 (vertices=11, convex hull=31, v0=108312) After retessellation of defect 75 (v0=108312), euler #=-45 (146993,439483,292445) : difference with theory (-41) = 4 CORRECTING DEFECT 76 (vertices=25, convex hull=20, v0=108524) After retessellation of defect 76 (v0=108524), euler #=-44 (146996,439497,292457) : difference with theory (-40) = 4 CORRECTING DEFECT 77 (vertices=25, convex hull=65, v0=110933) After retessellation of defect 77 (v0=110933), euler #=-43 (147008,439556,292505) : difference with theory (-39) = 4 CORRECTING DEFECT 78 (vertices=17, convex hull=55, v0=111411) After retessellation of defect 78 (v0=111411), euler #=-42 (147021,439616,292553) : difference with theory (-38) = 4 CORRECTING DEFECT 79 (vertices=28, convex hull=58, v0=112252) After retessellation of defect 79 (v0=112252), euler #=-41 (147039,439696,292616) : difference with theory (-37) = 4 CORRECTING DEFECT 80 (vertices=65, convex hull=56, v0=116457) After retessellation of defect 80 (v0=116457), euler #=-40 (147070,439818,292708) : difference with theory (-36) = 4 CORRECTING DEFECT 81 (vertices=43, convex hull=48, v0=119565) After retessellation of defect 81 (v0=119565), euler #=-39 (147081,439870,292750) : difference with theory (-35) = 4 CORRECTING DEFECT 82 (vertices=12, convex hull=31, v0=120858) After retessellation of defect 82 (v0=120858), euler #=-38 (147083,439885,292764) : difference with theory (-34) = 4 CORRECTING DEFECT 83 (vertices=21, convex hull=51, v0=122189) After retessellation of defect 83 (v0=122189), euler #=-37 (147093,439932,292802) : difference with theory (-33) = 4 CORRECTING DEFECT 84 (vertices=23, convex hull=35, v0=123172) After retessellation of defect 84 (v0=123172), euler #=-36 (147098,439957,292823) : difference with theory (-32) = 4 CORRECTING DEFECT 85 (vertices=24, convex hull=16, v0=124462) After retessellation of defect 85 (v0=124462), euler #=-35 (147099,439964,292830) : difference with theory (-31) = 4 CORRECTING DEFECT 86 (vertices=18, convex hull=21, v0=126537) After retessellation of defect 86 (v0=126537), euler #=-34 (147103,439981,292844) : difference with theory (-30) = 4 CORRECTING DEFECT 87 (vertices=163, convex hull=74, v0=127719) After retessellation of defect 87 (v0=127719), euler #=-32 (147132,440099,292935) : difference with theory (-29) = 3 CORRECTING DEFECT 88 (vertices=2608, convex hull=944, v0=128265) An extra large defect has been detected... This often happens because cerebellum or dura has not been removed from wm.mgz. This may cause recon-all to run very slowly or crash. if so, see https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/TopologicalDefect_freeview After retessellation of defect 88 (v0=128265), euler #=-27 (147576,441985,294382) : difference with theory (-28) = -1 CORRECTING DEFECT 89 (vertices=62, convex hull=97, v0=128984) After retessellation of defect 89 (v0=128984), euler #=-26 (147612,442138,294500) : difference with theory (-27) = -1 CORRECTING DEFECT 90 (vertices=34, convex hull=43, v0=129031) After retessellation of defect 90 (v0=129031), euler #=-25 (147619,442178,294534) : difference with theory (-26) = -1 CORRECTING DEFECT 91 (vertices=25, convex hull=26, v0=129123) After retessellation of defect 91 (v0=129123), euler #=-24 (147624,442201,294553) : difference with theory (-25) = -1 CORRECTING DEFECT 92 (vertices=30, convex hull=69, v0=129153) After retessellation of defect 92 (v0=129153), euler #=-23 (147640,442278,294615) : difference with theory (-24) = -1 CORRECTING DEFECT 93 (vertices=70, convex hull=63, v0=130172) After retessellation of defect 93 (v0=130172), euler #=-22 (147668,442390,294700) : difference with theory (-23) = -1 CORRECTING DEFECT 94 (vertices=8, convex hull=38, v0=132096) After retessellation of defect 94 (v0=132096), euler #=-21 (147670,442411,294720) : difference with theory (-22) = -1 CORRECTING DEFECT 95 (vertices=15, convex hull=17, v0=133013) After retessellation of defect 95 (v0=133013), euler #=-20 (147672,442419,294727) : difference with theory (-21) = -1 CORRECTING DEFECT 96 (vertices=20, convex hull=29, v0=134495) After retessellation of defect 96 (v0=134495), euler #=-19 (147677,442443,294747) : difference with theory (-20) = -1 CORRECTING DEFECT 97 (vertices=15, convex hull=37, v0=134570) After retessellation of defect 97 (v0=134570), euler #=-18 (147686,442486,294782) : difference with theory (-19) = -1 CORRECTING DEFECT 98 (vertices=24, convex hull=62, v0=134931) After retessellation of defect 98 (v0=134931), euler #=-17 (147695,442539,294827) : difference with theory (-18) = -1 CORRECTING DEFECT 99 (vertices=132, convex hull=139, v0=137618) After retessellation of defect 99 (v0=137618), euler #=-16 (147748,442761,294997) : difference with theory (-17) = -1 CORRECTING DEFECT 100 (vertices=183, convex hull=91, v0=141863) After retessellation of defect 100 (v0=141863), euler #=-15 (147786,442917,295116) : difference with theory (-16) = -1 CORRECTING DEFECT 101 (vertices=30, convex hull=61, v0=142813) After retessellation of defect 101 (v0=142813), euler #=-14 (147807,443007,295186) : difference with theory (-15) = -1 CORRECTING DEFECT 102 (vertices=412, convex hull=91, v0=144756) After retessellation of defect 102 (v0=144756), euler #=-13 (147822,443095,295260) : difference with theory (-14) = -1 CORRECTING DEFECT 103 (vertices=16, convex hull=23, v0=145164) After retessellation of defect 103 (v0=145164), euler #=-12 (147824,443108,295272) : difference with theory (-13) = -1 CORRECTING DEFECT 104 (vertices=115, convex hull=58, v0=145572) After retessellation of defect 104 (v0=145572), euler #=-11 (147836,443166,295319) : difference with theory (-12) = -1 CORRECTING DEFECT 105 (vertices=27, convex hull=85, v0=145965) After retessellation of defect 105 (v0=145965), euler #=-10 (147845,443230,295375) : difference with theory (-11) = -1 CORRECTING DEFECT 106 (vertices=29, convex hull=58, v0=148993) After retessellation of defect 106 (v0=148993), euler #=-9 (147860,443299,295430) : difference with theory (-10) = -1 CORRECTING DEFECT 107 (vertices=54, convex hull=70, v0=149160) After retessellation of defect 107 (v0=149160), euler #=-8 (147872,443366,295486) : difference with theory (-9) = -1 CORRECTING DEFECT 108 (vertices=37, convex hull=30, v0=149800) After retessellation of defect 108 (v0=149800), euler #=-7 (147877,443389,295505) : difference with theory (-8) = -1 CORRECTING DEFECT 109 (vertices=66, convex hull=38, v0=151036) After retessellation of defect 109 (v0=151036), euler #=-6 (147882,443418,295530) : difference with theory (-7) = -1 CORRECTING DEFECT 110 (vertices=47, convex hull=61, v0=152360) After retessellation of defect 110 (v0=152360), euler #=-5 (147899,443494,295590) : difference with theory (-6) = -1 CORRECTING DEFECT 111 (vertices=17, convex hull=35, v0=154207) After retessellation of defect 111 (v0=154207), euler #=-4 (147902,443518,295612) : difference with theory (-5) = -1 CORRECTING DEFECT 112 (vertices=29, convex hull=33, v0=155746) After retessellation of defect 112 (v0=155746), euler #=-3 (147908,443545,295634) : difference with theory (-4) = -1 CORRECTING DEFECT 113 (vertices=6, convex hull=28, v0=155993) After retessellation of defect 113 (v0=155993), euler #=-2 (147909,443557,295646) : difference with theory (-3) = -1 CORRECTING DEFECT 114 (vertices=65, convex hull=42, v0=156450) After retessellation of defect 114 (v0=156450), euler #=-1 (147913,443585,295671) : difference with theory (-2) = -1 CORRECTING DEFECT 115 (vertices=25, convex hull=69, v0=157683) After retessellation of defect 115 (v0=157683), euler #=0 (147924,443646,295722) : difference with theory (-1) = -1 CORRECTING DEFECT 116 (vertices=487, convex hull=140, v0=158176) After retessellation of defect 116 (v0=158176), euler #=0 (148043,444071,296028) : difference with theory (0) = 0 CORRECTING DEFECT 117 (vertices=63, convex hull=82, v0=158482) After retessellation of defect 117 (v0=158482), euler #=1 (148066,444172,296107) : difference with theory (1) = 0 CORRECTING DEFECT 118 (vertices=25, convex hull=52, v0=160509) After retessellation of defect 118 (v0=160509), euler #=2 (148075,444219,296146) : difference with theory (2) = 0 computing original vertex metric properties... storing new metric properties... computing tessellation statistics... vertex spacing 0.89 +- 0.30 (0.04-->13.28) (max @ vno 82328 --> 92757) face area -nan +- -nan (1000.00-->-1.00) performing soap bubble on retessellated vertices for 0 iterations... vertex spacing 0.89 +- 0.30 (0.04-->13.28) (max @ vno 82328 --> 92757) face area -nan +- -nan (1000.00-->-1.00) tessellation finished, orienting corrected surface... 431 mutations (38.0%), 702 crossovers (62.0%), 1683 vertices were eliminated building final representation... 15215 vertices and 0 faces have been removed from triangulation after topology correction, eno=2 (nv=148075, nf=296146, ne=444219, g=0) writing corrected surface to /home/basuia/Documents/mmvt_root/subjects/UC07/surf/lh.orig.premesh... defective orientation at vertex 142565(142566) with faces 280307 and 295773 defective orientation at vertex 142565(142848) with faces 280307 and 295765 defective orientation at vertex 142566(142565) with faces 280307 and 295773 defective orientation at vertex 142566(142849) with faces 280308 and 295887 defective orientation at vertex 142848(142565) with faces 280307 and 295765 defective orientation at vertex 142848(142849) with faces 280308 and 295888 defective orientation at vertex 142849(142566) with faces 280308 and 295887 defective orientation at vertex 142849(142848) with faces 280308 and 295888 0.005 % of the vertices (8 vertices) exhibit an orientation change removing intersecting faces 000: 1359 intersecting 001: 145 intersecting 002: 18 intersecting 003: 5 intersecting terminating search with 0 intersecting topology fixing took 9.0 minutes FSRUNTIME@ mris_fix_topology lh 0.1502 hours 4 threads #VMPC# mris_fix_topology VmPeak 1129128 mris_fix_topology -mgz -sphere qsphere.nofix -inflated inflated.nofix -orig orig.nofix -out orig.premesh -ga -seed 1234 UC07 rh reading spherical homeomorphism from 'qsphere.nofix' reading inflated coordinates from 'inflated.nofix' reading original coordinates from 'orig.nofix' using genetic algorithm with optimized parameters setting seed for random number genererator to 1234 ************************************************************* Topology Correction Parameters retessellation mode: genetic search number of patches/generation : 10 number of generations : 10 surface mri loglikelihood coefficient : 1.0 volume mri loglikelihood coefficient : 10.0 normal dot loglikelihood coefficient : 1.0 quadratic curvature loglikelihood coefficient : 1.0 volume resolution : 2 eliminate vertices during search : 1 initial patch selection : 1 select all defect vertices : 0 ordering dependant retessellation: 0 use precomputed edge table : 0 smooth retessellated patch : 2 match retessellated patch : 1 verbose mode : 0 ************************************************************* INFO: assuming .mgz format writing corrected surface to 'orig.premesh' dev dev before topology correction, eno=-410 (nv=168520, nf=337860, ne=506790, g=206) using quasi-homeomorphic spherical map to tessellate cortical surface... Correction of the Topology Finding true center and radius of Spherical Surface...done Surface centered at (0,0,0) with radius 100.0 in 11 iterations marking ambiguous vertices... 41215 ambiguous faces found in tessellation segmenting defects... 124 defects found, arbitrating ambiguous regions... analyzing neighboring defects... -merging segment 23 into 21 -merging segment 40 into 31 -merging segment 42 into 31 -merging segment 31 into 48 -merging segment 51 into 50 -merging segment 87 into 74 -merging segment 90 into 89 -merging segment 104 into 96 -merging segment 108 into 98 -merging segment 120 into 118 114 defects to be corrected 0 vertices coincident reading input surface /home/basuia/Documents/mmvt_root/subjects/UC07/surf/rh.qsphere.nofix... reading brain volume from brain... reading wm segmentation from wm... Reading original properties of orig.nofix Reading vertex positions of inflated.nofix Computing Initial Surface Statistics -face loglikelihood: -9.2517 (-4.6259) -vertex loglikelihood: -6.5878 (-3.2939) -normal dot loglikelihood: -3.5173 (-3.5173) -quad curv loglikelihood: -6.3616 (-3.1808) Total Loglikelihood : -25.7184 CORRECTING DEFECT 0 (vertices=151, convex hull=209, v0=94) After retessellation of defect 0 (v0=94), euler #=-90 (144497,426068,281481) : difference with theory (-111) = -21 CORRECTING DEFECT 1 (vertices=35, convex hull=59, v0=108) After retessellation of defect 1 (v0=108), euler #=-89 (144517,426153,281547) : difference with theory (-110) = -21 CORRECTING DEFECT 2 (vertices=10, convex hull=23, v0=1288) After retessellation of defect 2 (v0=1288), euler #=-88 (144518,426163,281557) : difference with theory (-109) = -21 CORRECTING DEFECT 3 (vertices=67, convex hull=97, v0=1421) After retessellation of defect 3 (v0=1421), euler #=-87 (144529,426242,281626) : difference with theory (-108) = -21 CORRECTING DEFECT 4 (vertices=27, convex hull=60, v0=1423) After retessellation of defect 4 (v0=1423), euler #=-86 (144543,426308,281679) : difference with theory (-107) = -21 CORRECTING DEFECT 5 (vertices=21, convex hull=62, v0=1771) After retessellation of defect 5 (v0=1771), euler #=-85 (144553,426361,281723) : difference with theory (-106) = -21 CORRECTING DEFECT 6 (vertices=40, convex hull=67, v0=1775) After retessellation of defect 6 (v0=1775), euler #=-84 (144570,426440,281786) : difference with theory (-105) = -21 CORRECTING DEFECT 7 (vertices=267, convex hull=246, v0=2689) After retessellation of defect 7 (v0=2689), euler #=-83 (144648,426785,282054) : difference with theory (-104) = -21 CORRECTING DEFECT 8 (vertices=30, convex hull=26, v0=3163) After retessellation of defect 8 (v0=3163), euler #=-82 (144649,426797,282066) : difference with theory (-103) = -21 CORRECTING DEFECT 9 (vertices=17, convex hull=24, v0=4640) After retessellation of defect 9 (v0=4640), euler #=-81 (144650,426808,282077) : difference with theory (-102) = -21 CORRECTING DEFECT 10 (vertices=13, convex hull=24, v0=4658) After retessellation of defect 10 (v0=4658), euler #=-80 (144651,426817,282086) : difference with theory (-101) = -21 CORRECTING DEFECT 11 (vertices=5, convex hull=13, v0=7070) After retessellation of defect 11 (v0=7070), euler #=-79 (144651,426823,282093) : difference with theory (-100) = -21 CORRECTING DEFECT 12 (vertices=18, convex hull=63, v0=7201) After retessellation of defect 12 (v0=7201), euler #=-78 (144660,426875,282137) : difference with theory (-99) = -21 CORRECTING DEFECT 13 (vertices=293, convex hull=321, v0=7246) After retessellation of defect 13 (v0=7246), euler #=-77 (144807,427482,282598) : difference with theory (-98) = -21 CORRECTING DEFECT 14 (vertices=60, convex hull=111, v0=9117) After retessellation of defect 14 (v0=9117), euler #=-76 (144837,427619,282706) : difference with theory (-97) = -21 CORRECTING DEFECT 15 (vertices=29, convex hull=57, v0=12973) After retessellation of defect 15 (v0=12973), euler #=-75 (144846,427665,282744) : difference with theory (-96) = -21 CORRECTING DEFECT 16 (vertices=37, convex hull=90, v0=14068) After retessellation of defect 16 (v0=14068), euler #=-74 (144869,427771,282828) : difference with theory (-95) = -21 CORRECTING DEFECT 17 (vertices=460, convex hull=240, v0=15934) After retessellation of defect 17 (v0=15934), euler #=-73 (144925,428045,283047) : difference with theory (-94) = -21 CORRECTING DEFECT 18 (vertices=13, convex hull=22, v0=19958) After retessellation of defect 18 (v0=19958), euler #=-72 (144926,428052,283054) : difference with theory (-93) = -21 CORRECTING DEFECT 19 (vertices=53, convex hull=80, v0=20214) After retessellation of defect 19 (v0=20214), euler #=-71 (144938,428125,283116) : difference with theory (-92) = -21 CORRECTING DEFECT 20 (vertices=21, convex hull=47, v0=20556) After retessellation of defect 20 (v0=20556), euler #=-70 (144944,428158,283144) : difference with theory (-91) = -21 CORRECTING DEFECT 21 (vertices=205, convex hull=167, v0=22949) After retessellation of defect 21 (v0=22949), euler #=-68 (145040,428521,283413) : difference with theory (-90) = -22 CORRECTING DEFECT 22 (vertices=128, convex hull=170, v0=25791) After retessellation of defect 22 (v0=25791), euler #=-67 (145128,428869,283674) : difference with theory (-89) = -22 CORRECTING DEFECT 23 (vertices=56, convex hull=86, v0=28735) After retessellation of defect 23 (v0=28735), euler #=-66 (145152,428985,283767) : difference with theory (-88) = -22 CORRECTING DEFECT 24 (vertices=214, convex hull=186, v0=29209) After retessellation of defect 24 (v0=29209), euler #=-66 (145217,429275,283992) : difference with theory (-87) = -21 CORRECTING DEFECT 25 (vertices=48, convex hull=55, v0=31316) After retessellation of defect 25 (v0=31316), euler #=-65 (145223,429311,284023) : difference with theory (-86) = -21 CORRECTING DEFECT 26 (vertices=172, convex hull=160, v0=33860) After retessellation of defect 26 (v0=33860), euler #=-64 (145290,429586,284232) : difference with theory (-85) = -21 CORRECTING DEFECT 27 (vertices=19, convex hull=54, v0=35083) After retessellation of defect 27 (v0=35083), euler #=-63 (145297,429629,284269) : difference with theory (-84) = -21 CORRECTING DEFECT 28 (vertices=110, convex hull=168, v0=35294) After retessellation of defect 28 (v0=35294), euler #=-62 (145369,429927,284496) : difference with theory (-83) = -21 CORRECTING DEFECT 29 (vertices=7, convex hull=30, v0=38552) After retessellation of defect 29 (v0=38552), euler #=-61 (145371,429944,284512) : difference with theory (-82) = -21 CORRECTING DEFECT 30 (vertices=158, convex hull=100, v0=48137) After retessellation of defect 30 (v0=48137), euler #=-60 (145421,430141,284660) : difference with theory (-81) = -21 CORRECTING DEFECT 31 (vertices=228, convex hull=192, v0=50263) After retessellation of defect 31 (v0=50263), euler #=-61 (145473,430402,284868) : difference with theory (-80) = -19 CORRECTING DEFECT 32 (vertices=96, convex hull=152, v0=50844) After retessellation of defect 32 (v0=50844), euler #=-60 (145535,430662,285067) : difference with theory (-79) = -19 CORRECTING DEFECT 33 (vertices=401, convex hull=152, v0=53085) After retessellation of defect 33 (v0=53085), euler #=-59 (145641,431051,285351) : difference with theory (-78) = -19 CORRECTING DEFECT 34 (vertices=96, convex hull=35, v0=59094) After retessellation of defect 34 (v0=59094), euler #=-58 (145650,431094,285386) : difference with theory (-77) = -19 CORRECTING DEFECT 35 (vertices=11, convex hull=24, v0=59110) After retessellation of defect 35 (v0=59110), euler #=-57 (145652,431106,285397) : difference with theory (-76) = -19 CORRECTING DEFECT 36 (vertices=70, convex hull=34, v0=61327) After retessellation of defect 36 (v0=61327), euler #=-56 (145661,431147,285430) : difference with theory (-75) = -19 CORRECTING DEFECT 37 (vertices=97, convex hull=45, v0=61598) After retessellation of defect 37 (v0=61598), euler #=-56 (145679,431222,285487) : difference with theory (-74) = -18 CORRECTING DEFECT 38 (vertices=78, convex hull=43, v0=63381) After retessellation of defect 38 (v0=63381), euler #=-55 (145688,431261,285518) : difference with theory (-73) = -18 CORRECTING DEFECT 39 (vertices=53, convex hull=102, v0=70854) After retessellation of defect 39 (v0=70854), euler #=-54 (145717,431388,285617) : difference with theory (-72) = -18 CORRECTING DEFECT 40 (vertices=51, convex hull=84, v0=73682) After retessellation of defect 40 (v0=73682), euler #=-54 (145747,431527,285726) : difference with theory (-71) = -17 CORRECTING DEFECT 41 (vertices=28, convex hull=53, v0=75699) After retessellation of defect 41 (v0=75699), euler #=-53 (145762,431589,285774) : difference with theory (-70) = -17 CORRECTING DEFECT 42 (vertices=29, convex hull=69, v0=77504) After retessellation of defect 42 (v0=77504), euler #=-52 (145775,431657,285830) : difference with theory (-69) = -17 CORRECTING DEFECT 43 (vertices=66, convex hull=76, v0=79551) After retessellation of defect 43 (v0=79551), euler #=-51 (145804,431777,285922) : difference with theory (-68) = -17 CORRECTING DEFECT 44 (vertices=9236, convex hull=4698, v0=79649) PIDs (6337 6340) completed and logs appended. Linux Ishita-Ubuntu 5.4.0-89-generic #100~18.04.1-Ubuntu SMP Wed Sep 29 10:59:42 UTC 2021 x86_64 x86_64 x86_64 GNU/Linux recon-all -s UC07 exited with ERRORS at Tue Nov 9 23:06:01 EST 2021 To report a problem, see http://surfer.nmr.mgh.harvard.edu/fswiki/BugReporting